A beginners guide to the math that powers machine learning – The Next Web

How much math knowledge do you need for machine learning and deep learning? Some people say not much. Others say a lot. Both are correct, depending on what you want to achieve.

There are plenty of programming libraries, code snippets, and pretrained models that can get help you integrate machine learning into your applications without having a deep knowledge of the underlying math functions.

But theres no escaping the mathematical foundations ofmachine learning. At some point in your exploration and mastering of artificial intelligence, youll need to come to terms with the lengthy and complicated equations that adorn AI whitepapers and machine learning textbooks.

In this post, I will introduce some of my favorite machine learning math resources. And while I dont expect you to have fun with machine learning math, I will also try my best to give you some guidelines on how to make the journey a bit more pleasant.

Khan Academys online courses are an excellent resource to acquire math skills for machine learning

Many machine learning books tell you that having a working knowledge of linear algebra. I would argue that you need a lot more than that. Extensive experience with linear algebra is a must-havemachine learning algorithms squeeze every last bit out of vector spaces and matrix mathematics.

You also need to know a good bit of statistics and probability, as well as differential and integral calculus, especially if you want to become more involved indeep learning.

There are plenty of good textbooks, online courses, and blogs that explore these topics. But my personal favorite isKhan Academys math courses. Sal Khan has done a great job of putting together a comprehensive collection of videos that explain different math topics. And its free, which makes it even better.

Although each of the videos (which are also available on YouTube) explain a separate topic, going through the courses end-to-end provides a much richer experience.

I recommend thelinear algebracourse in particular. Here, youll find everything you need about vector spaces, linear transformations, matrix transformations, and coordinate systems. The course has not been tailored for machine learning, and many of the examples are about 2D and 3D graphic systems, which are much easier to visualize than the multidimensional spaces of machine learning problems. But they discuss the same concepts youll encounter in machine learning books and whitepapers. In the course are some hidden gems like least square calculations and eigenvectors, which are important topics in machine learning.

The calculus course are a bit more fragmented, but it might be a good feature for readers who already have a strong foundation and just want to brush up their skills. Khan includes precalculus, differential calculus, and integral calculus courses that cover the foundations. Themultivariable calculus coursediscusses some of the topics that are central to deep learning, such as gradient descent and partial derivatives.

There are also several statistics courses in Khan Academys platform, and there are some overlaps between them. They all discuss some of the key concepts you need in data science and machine learning, such as random variables, distributions, confidence intervals, and the difference between continuous and categorical data. I recommend thecollege statistics course, which includes some extra material that is relevant to machine learning, such as the Bayes theorem.

To be clear, Khan Academys courses are not a replacement for the math textbook and classroom. They are not very rich in exercises. But they are very rich in examples, and for someone who just needs to blow the dust off their algebra knowledge, theyre great. Sal talks very slowly, probably to make the videos usable for a wider audience who are not native English speakers. I run the videos on 1.5x speed and have no problem understanding them, so dont let the video lengths taunt you.

Vanilla algebra and calculus are not enough to get comfortable with the mathematics of machine learning. Machine learning concepts such as loss functions, learning rate, activation functions, and dimensionality reduction are not covered in classic math books. There are more specialized resources for that.

My favorite isMathematics for Machine Learning. Written by three AI researchers, the provides you with a strong foundation to explore the workings of different components of machine learning algorithms.

The book is split into two parts. The first part is mathematical foundations, which is basically a revision of key linear algebra and calculus concepts. The authors cover a lot of material in little more than 200 pages, so most of it is skimmed over with one or two examples. If you have a strong foundation, this part will be a pleasant read. If you find it hard to grasp, you can combine the chapters with select videos from Khans YouTube channel. Itll become much easier.

The second part of the book focuses on machine learning mathematics. Youll get into topics such as regression, dimensionality reduction, support vector machines, and more. Theres no discussion ofartificial neural networksand deep learning concepts, but being focused on the basics makes this book a very good introduction to the mathematics of machine learning.

As the authors write on their website: The book is not intended to cover advanced machine learning techniques because there are already plenty of books doing this. Instead, we aim to provide the necessary mathematical skills to read those other books.

For a more advanced take on deep learning, I recommendHands-on Mathematics for Deep Learning. This book also contains an intro on linear algebra, calculus, and probability and statistics. Again, this section is for people who just want to jar their memory. Its not a basic introductory book.

The real value of this book comes in the second section, where you go into the mathematics of multilayer perceptrons,convolutional neural networks(CNN), andrecurrent neural networks(RNN). The book also goes into the logic of other crucial concepts such as regularization (L1 and L2 norm), dropout layers, and more.

These are concepts that youll encounter in most books on machine learning and deep learning. But knowing the mathematical foundations will help you better understand the role hyperparameters play in improving the performance of your machine learning models.

A bonus section dives into advanced deep learning concepts, such as the attention mechanism that has made Transformers so efficient and popular, generative models such as autoencoders andgenerative adversarial networks, and the mathematics oftransfer learning.

Agreeably, mathematics is not the most fun way to start machine learning education, especially if youre self-learning. Fortunately, as I said at the beginning of this article, you dont need to begin your machine learning education by poring over double integrals, partial derivatives, and mathematical equations that span a pages width.

You can start with some of the more practical resources on data science and machine learning. A good introductory book isPrinciples of Data Science, which gives you a good overview of data science and machine learning fundamentals along with hands-on coding examples in Python and light mathematics.Hands-on Machine Learning andPython Machine Learningare two other books that are a little more advanced and also give deeper coverage of the mathematical concepts. UdemysMachine Learning A-Zis an online course that combines coding with visualization in a very intuitive way.

I would recommend starting with one or two of the above-mentioned books and courses. They will give you a working knowledge of the basics of machine learning and deep learning and prepare your mind for the mathematical foundations. Once you know have a solid grasp of different machine learning algorithms, learning the mathematical foundations becomes much more pleasant.

As you master the mathematics of machine learning, you will find it easier to find new ways to optimize your models and tweak them for better performance. Youll also be able to read the latest cutting edge papers that explain the latest findings and techniques in deep learning, and youll be able to integrate them into your applications. In my experience, the mathematics of machine learning is an ongoing educational experience. Always look for new ways to hone your skills.

This article was originally published by Ben Dickson on TechTalks, a publication that examines trends in technology, how they affect the way we live and do business, and the problems they solve. But we also discuss the evil side of technology, the darker implications of new tech and what we need to look out for. You can read the original article here.

Published October 2, 2020 10:00 UTC

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A beginners guide to the math that powers machine learning - The Next Web

BullGuard launches new anti-malware range with machine learning and multi-layer protection – BetaNews

BullGuard has announced its new 2021 security suite, featuring Dynamic Machine Learning, which continuously monitors all processes on a user's device, enabling real-time detection and blocking of potentially malicious behavior before it can do damage.

The new suite also offers Multi-Layered Protection which uses six layers -- Safe Browsing, Dynamic Machine Learning, Sentry Protection for Zero-Day Malware, an On-Access AV Engine, a Firewall and a Vulnerability Scanner -- to defend the users devices from malware, without the need for user interaction.

These layers work together to create a buffer between the internet and each device BullGuard 2021 is installed on, designed to catch inbound and local malware, any erroneous outbound communication to the internet, phishing scams and more.

BullGuard 2021 also offers improved application performance while reducing system resource usage, including significantly reduced virus definition file sizes. Other enhancements include identity protection, with additional support for international phone numbers and bank accounts, that ensures accurate monitoring of dark web platforms where stolen user data is sold or traded. There's also an improved Game Booster that now includes support for anti-cheat engines and uninterrupted video performance while broadcasting during gameplay.

"Unlike the majority of other cybersecurity solutions, BullGuard's Dynamic Machine Learning protection continually monitors all processes on your device, enabling real-time detection and blocking of potentially malicious behavior, even if malware attempts to cut your internet connection," says Paul Lipman, CEO of BullGuard. "BullGuard 2021 is ideal for consumers who want 'set-it-and-forget-it' cybersecurity that works behind-the-scenes to provide the best endpoint protection against today's known and zero-day threats."

The product line is being offered in three versions:

You can find out more on the BullGuard site.

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BullGuard launches new anti-malware range with machine learning and multi-layer protection - BetaNews

Q&A: How machine learning helps scientists hunt for particles, wrangle floppy proteins and speed discovery – Stanford University News

For example, SLAC scientists have already used machine learning techniques tooperate accelerators more efficiently, to speed up thediscovery of new materials, and to uncoverdistortions in space-time caused by astronomical objectsup to 10 million times faster than traditional methods.

The term machine learning broadly refers to techniques that let computers learn by example by inferring their own conclusions from large sets of data, as opposed to following a predetermined set of steps or rules. To take advantage of these techniques, SLAC launched a machine learning initiative in 2019 that involves researchers across virtually all of the labs disciplines.

An accelerator physicist by training, Daniel Ratner has worked to apply machine learning approaches to accelerators at SLAC for many years and now heads up the initiative. In this Q&A, he discusses what machine learning can do and how SLAC is uniquely equipped to advance the use of machine learning in fundamental science research.

Machine learning programs solve tasks by looking for patterns in examples. This is similar to the way that humans learn. So machine learning tends to be effective at tasks that humans are good at, but it's hard to explain why.

For instance, you can teach your teenager how to drive a car by example. But it's hard to write down a set of rules for how to drive a car in every possible situation you might encounter when you're driving. Thats the kind of case where machine learning has been successful. Just by watching someone drive a car for long enough, a machine learning model can begin to learn the rules of driving.

It usually boils down to learning how to do something by watching enough data.

It's a different conceptual approach to problems. Rather than writing a sophisticated computer program for an entire complex data analysis process by hand, machine learning shifts the emphasis to developing a data set of examples and a way to evaluate solutions. At that point, I can hand over my raw data to a machine learning model and train it to predict solutions for new data it hasnt seen before. You can think of it as a way of avoiding that onerous, expensive programming by extracting rules hidden in a data set.

Lets say were doing some high-energy physics, analyzing particle tracks in a detector, which is how particle physicists learn about natures fundamental components. Rather than writing algorithms by hand that manage each part of the analysis removing noise, finding tracks and identifying what all the particles are that created them and building the analysis process up bit by bit, we can just take a big chunk of simulated data and learn how to do that entire analysis pipeline with a single big neural network, a machine learning technique inspired by human neural systems. And in practice, the machine learning methods often out-perform their human-written counterparts.

In science, the area where machine learning has gotten the most press is in data analysis. A typical task would be: I have a big data set and I want to extract some science from it. And certainly we do a lot of that as well at SLAC. But theres actually a lot more that we can do.

Because we run all these big scientific facilities, we think about how machine learning applies not just to data analysis, but to how scientific experiments at these facilities work.

We can use machine learning to address questions like How do I design a new accelerator?, Once Ive built it, how can I run it better? and How can I identify or even predict faults?

For example, were building the next-generation X-ray laser LCLS-II, which will generate terabytes of data per second. A new project led by SLAC will develop machine learning models on the facilitys detectors to analyze this enormous amount of data in real time. This model can be flexible and adapt to the individual needs of every future user of LCLS-II.

Every level of a scientific experiment from design to operations to experimental procedure to data analysis can be changed with machine learning. I think that's a particular emphasis for a place like SLAC, where our bread and butter is running big facilities.

One example is in improving our ability to analyze how a protein molecule changes over time on the atomic level. A protein is a floppy, flexible thing, and that motion is essential to the proteins function. Rather than trying to learn the average structure of a protein by taking a blurred picture of a moving object, we would like to make a movie and actually watch how that molecule is moving. Theres been some very interesting research on using machine learning models to make these protein movies.

As an example of the particle tracking idea mentioned earlier, we have a group at SLAC applying machine learning to neutrino detectors. The task here is to look for very small tracks when particles fly through huge three-dimensional detectors. The scientists have been doing that using something called sparse models, which speed up the learning process by not allocating computational resources to empty space without any tracks. These sparse models are both faster to train and more accurate compared to the standard neural networks developed for the analysis of everyday images.

And it turns out that we can actually use that same concept in very different areas. For example, in materials science, you might want to be able to identify a single atom and ignore the vast area around that atom. So even with different scientific goals in mind, we can use the same boundary-pushing machine learning models. Having the machine learning initiative allows all these different people to talk to each other, share experiences and ideas, and make progress faster.

Ive always been intrigued by the possibility of extracting valuable information from seemingly random data. I think this search for structure in noisy data is what draws me to science in general. Theres also a lot of overlap with the non-machine learning science projects Ive chosen the last 15 years.

Science is a place where you often have large datasets and ask concrete questions, and that is exactly the setup that makes machine learning successful. And machine learning allows us to ask entirely different types of questions that we couldnt before. Thats going to lead to very exciting science.

There are many people at SLAC who have been doing machine learning for a long time. Now were codifying our lab-wide approach to machine learning and providing more structure and support for everyone who wants to apply these new tools in their research. My goal for our initiative is to provide a central locus for people to discuss, collaborate and come up with new ideas and educate themselves. This lets us scale up machine learning efforts across the lab and make everyone more effective. We have this big community of people who are actively using machine learning every day in their science research, and that number is only going to grow.

One of the things we emphasize is that the goal of machine learning is not to do what we're doing today and do it 10% better. We want to do completely new science. We want to do things 10 times better, 100 times better, a million times better. And we want to start seeing examples of that in the next couple of years and enable science at SLAC that wasnt possible before.

Machine learning projects at SLAC are supported by DOEs Office of Science and the Office of Energy Efficiency and Renewable Energy. Machine learning is a DOE priority, and the department recently established an Artificial Intelligence and Technology Office.

For questions or comments, contact the SLAC Office of Communications atcommunications@slac.stanford.edu.

SLAC is a vibrant multiprogram laboratory that explores how the universe works at the biggest, smallest and fastest scales and invents powerful tools used by scientists around the globe. With research spanning particle physics, astrophysics and cosmology, materials, chemistry, bio- and energy sciences and scientific computing, we help solve real-world problems and advance the interests of the nation.

SLAC is operated by Stanford University for the U.S. Department of Energys Office of Science. The Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time.

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Q&A: How machine learning helps scientists hunt for particles, wrangle floppy proteins and speed discovery - Stanford University News

How machine learning is bringing National Library of Scotland’s maps to life – The Scotsman

LifestyleOutdoorsWebsites belonging to Scotland's national records offices hold a treasure trove of data but to get any value from these sites you have to know what you are looking for.

Friday, 2nd October 2020, 9:05 pm

What if machine learning meant that you didn't have to have a definitive starting point and the reams of records in the archives could be explored and enjoyed visually?

That is the vision of Martin Disley who has been creating datasets from across the National Library of Scotland's (NLS) map collection.

His project, which is part of the Creative Informatics Resident Entrepreneur project at the University of Edinburgh, curated datasets of images previously scanned by the NLS to feed a machine learning model.The newly-created machine learning model then creates 'fake' versions of the images that it is trained upon.

The generated output from this process can be animated to produce visions of machines dreaming, in this case the fake maps animated and brought to life. This has the effect of synthesising these large collections down in short videos.

Fake maps and towns can be created from the model and then animated.

When the animation starts with a small town and ends with a large developed town, the viewer can watch the town grow in an organic manner as the model has been trained on how towns of every size grow over time.

He said: "People can view thousands of images online but this can quickly become overwhelming and it is a struggle to get people to get people to engage with the content.

We are working on a tool that will allow users to interact with the model, to be able to control what it produces.

The technology which drives Martin's machine learning model is based on the GAN machine learning architecture which gained national attention when it was used to create the website thispersondoesnotexist.com.

Over 70,000 facial images from Flickr were used to train the model meaning it was able to learn patterns in human face composition and then create new faces.

Martin said: "If you consider maps, you are already starting with a fake. It is a pictorial representation of reality.

The models I have made have learnt the grammar of these maps; you can read these fake maps like you can read any of the originals. You are able to build an internal representation of the map in your head; you can imagine what these places might look like.

Martin said the process of creating his model was one of fine tuning having started with a large dataset and then whittling out the images of maps that were creating bad results.

"When you are training the model you get to see the dataset in motion.

"As I go through the dataset I take out what I don't like and pick points that are producing interesting results.

"The National Library are excited about the potential for the increased public engagement that synthesising these overwhelmingly large collections into visually exciting media might bring

Martin Disley is a participant in Creative Informatics Resident Entrepreneur project which delivered by the University of Edinburgh in partnership with Edinburgh Napier University, CodeBase and Creative Edinburgh and is one of nine programmes across the UK that make up the Creative Industries Clusters Programme, funded by the Arts and Humanities Research Council as part of the UK Governments Industrial strategy. Creative Informatics is part of the Edinburgh and South East Scotland City Region Deal initiative (DDI Programme) and is also supported by the Scottish Funding Council.

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How machine learning is bringing National Library of Scotland's maps to life - The Scotsman

Global Machine Learning-as-a-Service (MLaaS) Market Size 2020 | Covid-19 Analysis, Trends, Top Key Players, Statistics, Growth Opportunities and…

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WikiLeaks’ Assange won’t get US extradition ruling this year – The Associated Press

LONDON (AP) WikiLeaks founder Julian Assange will likely spend the rest of 2020 inside a British prison cell before finding out whether he can be sent to the United States to face espionage charges, the judge in his extradition hearing said Thursday.

After hearing nearly four weeks of evidence at Londons Old Bailey courthouse, District Judge Vanessa Baraitser said she would deliver her decision on whether to grant a U.S. extradition request for Assange at 10 a.m. on Jan. 4. Assange is fighting extradition.

The judges ruling wont necessarily end the proceedings. Whichever side loses is expected to appeal. Theres also the possibility of a change in U.S. policy should Joe Biden defeat President Donald Trump in the Nov. 3 U.S. presidential election.

Unless any further application for bail is made, and between now and the 4th of January, you will remain in custody for the same reasons as have been given to you before, Baraitser told Assange, who was sitting behind a security screen at the back of the hearing courtroom.

The judge previously denied Assange bail over fears he is a flight risk. Assange jumped bail in 2012 when he sought asylum at the Ecuadorian Embassy in London, where he stayed for seven years before being evicted and arrested. He has been in custody at Belmarsh prison in London since April 2019 and is expected to appear in court via video link every 28 days between now and the Jan. 4 ruling.

U.S. prosecutors have indicted the 49-year-old Assange on 17 espionage charges and one charge of computer misuse over WikiLeaks publication of secret American military documents a decade ago largely relating to the wars in Afghanistan and Iraq.

Following the adjournment on Thursday, Stella Moris, Assanges fiance and the mother of his two young children, said, Julian and I would like to thank everyone for the kindness that has been shown over the past few weeks.

Its a fight for Julians life, a fight for press freedom and a fight for the truth, Moris said outside the court.

Now that lawyers have finished presenting evidence, Assanges defense team has asked for another four weeks to submit its closing argument. That will be followed two weeks later by the closing argument of the lawyers prosecuting on behalf of the U.S. government.

The judge has an abundance of evidence to trawl through in a hearing that was delayed by the onset of the coronavirus pandemic. Except for an early virus exposure scare and occasional outbursts from the usually face-masked Assange, the hearing proceeded smoothly.

The charges against Assange carry a maximum sentence of 175 years in prison. Lawyers acting on behalf of the U.S. government say Assange committed serious crimes that put peoples lives in danger, allegations his fiance disputed.

Under oath, the prosecution concedes that it has no evidence that a single person has ever come to any physical harm because of these publications, Moris said. Let me repeat that: there is no evidence that a single person has ever come to any physical harm because of these publications.

Assanges defense team argued he is entitled to First Amendment protections for the publication of leaked documents that exposed U.S. military wrongdoing and that the extradition request was politically motivated.

The London court heard from an array of witnesses, who pronounced on issues of huge importance and substance, such as the freedom of the press and government-sanctioned torture.

Julian Assanges actions, which have been characterized as criminal, are actions that expose power to sunlight, renowned U.S. linguist and scholar Noam Chomsky said.

Other witnesses relayed more shadowy and sometimes comic matters of intrigue during his time at WikiLeaks and at the Ecuadorian Embassy,

According to one witness, Assange binge-watched the suicide of the former Bosnian Croat general, Slobodan Praljak, at a U.N. court three years ago.

Defense lawyers said Assange was suffering from wide-ranging mental health issues, including suicidal tendencies, that could be exacerbated if he is placed in inhospitable prison conditions in the U.S. They said Assanges mental health deteriorated while he took asylum inside the embassy and that he was diagnosed with an autism spectrum disorder.

His legal team argued that Assange would very likely face solitary confinement in the U.S. immediately that would put him at a heightened risk of suicide. They also said that if convicted, Assange would most likely be sent to the notorious ADX Supermax prison in Colorado, a facility labeled by a former warden as a fate worse than death and inhabited by the likes of Unabomber Ted Kaczynski and Mexican drug lord Joaquin El Chapo Guzman.

Lawyers acting on behalf of the U.S. government argued that Assanges mental state was not as poor as described and said he wouldnt be subject to improper conditions before or after any trial.

Assange has attracted the support of high-profile figures, including actress Pamela Anderson and rapper M.I.A. The dissident Chinese contemporary artist Ai Weiwei also staged a silent protest outside the court.

Daniel Ellsberg, perhaps the most famous whistleblower in living memory, argued that they had very comparable political opinions.

The 89-year-old, widely credited for helping to bring about an end to the Vietnam War through his leaking of the so-called Pentagon Papers in 1971, said the American public needed urgently to know what was being done routinely in their name, and there was no other way for them to learn it than by unauthorized disclosure.

There are clear echoes between Assange and Ellsberg, who leaked over 7,000 pages of classified documents to the press, including The New York Times and The Washington Post. He was subsequently put on trial on 12 charges in connection with violations of the Espionage Act, which were punishable by up to 115 years in prison. The charges were dismissed in 1973 because of government misconduct against him.

Assange will be hoping that developments within the U.S. government over the coming weeks will lead to a similar outcome for him before any judgment from the London court.

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WikiLeaks' Assange won't get US extradition ruling this year - The Associated Press

Why You Should Care About the Extradition of Julian Assange – The Intercept

Julian Assanges impending extradition to the United States could set a dangerous new precedent in international law by allowing powerful governments to demand the handing-over of foreign journalists who publish information they deem damaging to their interests. Ryan Grim discusses the Assange case with Kevin Gosztola of Shadowproof. Then, Dana Gottesfeld describes the plight of her husband Martin, a hacktivist and human rights activist currently serving time at a prison in Indiana, similar to the one Assange could end up in.

Ryan Grim: Earlier this week, the nations beleaguered voters were subjected to a debate the likes of which had never been seen before on a presidential stage.

Joe Biden: I want to make sure I want to make the President

President Donald J. Trump: You graduated last in your class, not first in your class.

Chris Wallace: Can you let him finish, sir?

DJT: radical left well, listen.

JB: Would you shut up, man?

DJT: Listen, who is on your list, Joe? Who is on your list?

CW: Gentleman, I think weve ended this.

RG: But on the plus side, we learned something interesting about Europeans.

DJT: You know in Europe they live in, forest cities, they call forest cities. They maintain their forests. They manage their forests. I was with the head of a major country. Its a forest city.

RG: But today on the show, were going to flee the United States and head to a courtroom in London, where the Trump administration has launched the most consequential fight over global press freedom in several generations. The press itself has been almost entirely silent about it. So lets do something about that.

Im Ryan Grim. Today on Deconstructed: Why you should care about the impending extradition of Julian Assange to the United States.

In that courtroom in London, over the past month, a magistrate has been reviewing a request by U.S. prosecutors, under the direction of Attorney General William Barr, to extradite Wikileaks founder Julian Assange an Australian citizen and try him, in the United States, under the Espionage Act. He could face life in prison, in solitary confinement, in a Colorado or Indiana supermax prison.

Newscaster: The arrest was made on behalf of the United States, an effort Assanges lawyers describe as an unprecedented effort to extradite a foreign journalist.

RG: That extradition hearing is now in its fourth week. At issue is whether Assange broke the law in obtaining and publishing leaked documents from former U.S. Army intelligence analyst Chelsea Manning. Daniel Ellsberg, who leaked the Pentagon Papers during the Nixon administration, made an appearance at the hearing.

So did Khaled Al-Masri, the German-Lebanese man who was mistakenly abducted and handed over to the CIA in 2003, then subjected to gruesome torture by the Bush administration. We only know Al-Masris story in full thanks to Assange and Wikileaks. Assanges case deals with basic questions about the nature of a free press, justice for victims of torture, and accountability for powerful governments.

So why the silence? You might think that liberals would leap at the opportunity to defend the press against a wannabe authoritarian like Trump. His constant assaults on the news media have created a new veneration for journalism on the American left and look, as a journalist myself, Im all for that. But when it comes to Assange and Wikileaks, the veneration ends. Why?

The Obama administration came close to prosecuting Assange. But they finally decided, in December 2013, that they couldnt overcome what they called The New York Times problem. Put simply: How can the government charge Wikileaks for publishing sensitive information without also prosecuting The New York Times? Now, the Obama administration understood what it would mean to go after the Times, so ultimately they backed off of Wikileaks.

The Trump administration? No, they have no such scruples. Trump has already said he thinks that U.S. laws around press freedom are too generous to the fake news media. Respect for the fourth estate is definitely not holding him back.

But the main reason liberals are reluctant to defend the founder of Wikileaks is his relationship to the Clintons. In 2016, Assange released thousands of emails from the inbox of Hilary Clinton campaign chair John Podesta, producing endless damaging stories in the final weeks of the campaign. Among other things, the release included excerpts from Clintons private speeches to Goldman Sachs, which she had previously refused to release. For sure, Democrats have good reason to believe the publication of those emails played a major role in her loss. And so as the chains have tightened around Assange, theyve mostly looked the other way. After all, he was just getting what he had coming.

Back in 2016, when Wikileaks was disseminating embarrassing information about his rival, Donald Trump was their biggest fan.

DJT: Oh, we love WikiLeaks. Boy, they have really

DJT: Wikileaks!

DJT: Its been amazing whats coming out on WikiLeaks.

DJT: This WikiLeaks is like a treasure trove!

DJT: This Wikileaks is unbelievable.

DJT: I love reading those WikiLeaks.

DJT: The wonder of Wikileaks. Weve learned so much from WikiLeaks.

But after a few years in power, his attitude? A little bit different.

Reporter: Do you still love WikiLeaks?

DJT: I know nothing about WikiLeaks. Its not my thing.

DJT: WikiLeaks is a hoax, just like everything else.

DJT: WikiLeaks, etc. Thats not my deal in life. You know, in other words, I dont know about Wikileaks, it was a strange name.

RG: Supporters of the prosecution of Assange make a number of arguments: That Assange is not a real journalist. Hes a hacker. Hes a traitor. He recklessly endangered lives and so he deserves no protection as a journalist. All of this is wrong.

The First Amendment isnt worth the parchment its written on if its not respected, and defended, in the broader culture of the United States. People have to support it. Once that support erodes, it tends not to come back. Thats why authoritarians, when they want to curtail a particular freedom, usually find the most unsympathetic target they can, hoping nobody will come to his defense. Then once a new precedent is established, all bets are off. With Assange, Trump and Barr think theyve found just such a man. Its up to us not to take the bait.

[Musical interlude.]

RG: In a moment were going to talk to Dana Gottesfeld, whose husband, Marty Gottesfeld, a hacker, activist, and writer, is being held incommunicado in an Indiana prison that may soon play host to Assange. But first I want to speak with the journalist Kevin Gosztola of the outlet Shadow Proof, who has covered the hearing since it opened four weeks ago. Kevin, welcome to Deconstructed.

Kevin Gosztola: Yeah, thanks for having me.

RG: So Kevin, can you start out with a quick rundown of what a hearing like this looks like in a pandemic, what its like to cover it?

KG: Yeah, this has been a tremendously difficult hearing, cumbersome for the court to put on. This is being done or, this was done, I believe by the time people listen to this interview, we will have concluded the witness testimony in its entirety, and the defense will then be preparing their closing arguments for the judge, for Vanessa Baraitser to review and ultimately decide whether to approve the extradition of Julian Assange.

But this Old Bailey criminal courthouse, a very old building, a fixture in London, a Dickensian kind of courthouse as it has been described to me, is one that had to be able to manage essentially bringing on dozens of witnesses for the defense who could testify using a video platform, and then simultaneously be able to bring in press who could follow video links, and, because of the pandemic, social distance within this courthouse.

RG: I want to start with the testimony of Trevor Tim, who actually writes for The Intercept on occasion, and you covered his appearance before the court. Thats when the real debate kind of over, you know, the nature of journalism began. What was the argument that Tim presented to the court?

KG: Trevor Tim took the stand and, importantly, he described how theres over 70 media outlets that have adopted the SecureDrop system, this submission system in which you can receive leaks anonymously, and hopefully protect the identity of people who are providing documents, and that there are well established media outlets that are using this now, like The New York Times, The Washington Post, USA Today. And that there are organizations like the International Consortium for Investigative Journalists that would post on their website leak to us, that they would advertise. So they are soliciting leaks, they are asking people to give them information and it doesnt say, you know, it doesnt have a disclaimer do not provide classified information to us. Its acceptable to provide all information to these outlets, they will investigate and try to verify those documents.

And so the point being that WikiLeaks truly was a pioneer of this method of saying that we were going to accept documents from sources anonymously, and we will work to authenticate and verify those documents, and then we will publish them.

I think the key thing about Trevor Tims testimony is destigmatizing the work of WikiLeaks, or even demystifying it. Because what you have through the U.S. governments targeting of Wikileaks over the past decade is a concerted effort to make it seem like what WikiLeaks does is not journalism. And so the counter to that through the defenses case is to make it abundantly clear that this is not reasonable; that in fact, everything that WikiLeaks does, from when it accepts the documents, when it tries to authenticate them, to when it makes media partnerships, to also make sure that names are redacted, to make sure that sensitive details are understood fully before the documents are published. And I think you see that this is the way to keep investigative journalism robust in the 21st century.

RG: I thought Trevors point was interesting that The New York Times does not get a press badge from the U.S. government. You know, it isnt, and it shouldnt be, up to the U.S. government to decide who is and who is not a journalist.

And the idea of who is or is not a responsible journalist is different from what is illegal or legal conduct, which I also thought was important because the prosecution wants to say: Well, hes an irresponsible person, so therefore, he doesnt have these protections. And the counter is no, its not up to the government to say whats responsible or irresponsible journalism. You know, the government creates laws, and if the laws are violated, then you can start your prosecution. But if not, you cant. And its never been against the law to publish classified information. Its against the law to leak it, if you have access to it. But its not against the law to publish it.

Thats why I thought it was also really compelling that Daniel Ellsberg testified. You know, Ellsberg has been really put on a pedestal over the last 10 or 20 years as the kind of whistleblower who did it right. And theres a real effort among people to separate Ellsberg from people even like Edward Snowden, or from Assange to say that these are people who behave responsibly in trying to inform the public, and then these are people who behave irresponsibly and so, therefore, theyre criminals. Now Edward Snowden is a source, Assange is a publisher, but what did Ellsberg tell the court and why was his testimony relevant?

KG: In my view, Ellsberg testimony was significant because he unraveled or he undermined the kind of dichotomy that is usually perpetuated by the mass media in the sense that hes talked about as the good leaker, and then, even though Julian Assange isnt technically a leaker, he would be referred to as the bad leaker.

But Ellsberg made it very clear that he was no different from Assange in what he decided to disclose to the press, or what he decided to disclose to the public, for that matter. Because out of the 4000 pages, it contained thousands of names of Americans, Vietnamese, and North Vietnamese. And he even spoke in detail about a clandestine CIA officer whose name was revealed. And the reason why he didnt hold back any names, he told the prosecutor was because he didnt want anybody to think as they looked through the redactions in the papers, that perhaps hiding behind these black bars was a good justification for being at war in Vietnam. He wanted to make sure that no U.S. official could lie and deceive the public into believing that Ellsberg was hiding a reasonable case for remaining in Vietnam.

RG: There was an interesting exchange between Ellsberg and the prosecutor where Ellsberg was trying to lay out that theres no evidence whatsoever that anybody has actually been harmed as a result of the WikiLeaks releases. And the judge was stopping him from saying that, which actually brought an intervention from Assange, himself, who you say is kind of in a plexiglass cage in the corner. So how did Assange respond to that, and can he be heard? Or can you only just tell that hes agitating?

KG: Yeah. So over video, its difficult to understand and hear him, though I can make out some words, during the course of these proceedings.

Most of the reporting on Assange is interruptions I dont really call them disruptions, because I think its fairly frustrating. We need to be sensitive to what has gone on with his due process rights over the course of the extradition case. I believe Americans can appreciate how unusual it is to be separated from your attorneys and not be able to quickly consult with your legal team.

Normally, a defendant like Assange, if he was just in the United States, would be able to lean over and talk to his attorney. And very quickly, that attorney would be able to ask the question that needs to be put to Daniel Ellsberg. And in fact, he cant do that without shouting from the back of the courtroom from this glass box, that, by the way, I know back in February of this year, the judge refused to allow him to leave so that he could join his legal team, even though the prosecution said that they were neutral and did not care if Julian Assange was permitted to sit with his attorneys during proceedings. As a way of enforcing her authority over Julian Assange and this extradition case, shes kept him in the dock, or as we call it, the glass box.

RG: Right.

KG: And so essentially, if Im recalling this correctly, I believe that Assange was just insistent that nobody had been put at risk by these disclosures. And, you know, some of these proceedings, hes also just been frustrated at the way the prosecutors treat the witnesses, believing that the prosecutor isnt letting witnesses speak. Thats an important thing as well.

But but just close the loop here with Ellsberg, you know, he made the correct argument, which is to say that, when you go back to Chelsea Mannings trial, there was a witness I forget exactly what his title was but I know his last name was Carr. And he took the stand and made a claim in the middle of the courtroom I remember this because I was there covering it at Fort Meade he made the claim that someone in the Taliban had executed someone who was named in a WikiLeaks document. And then the defense objected, and there was back and forth, and then finally, it was determined, and they conceded, that the Taliban had just lied, they had said it was but that person was never named in the WikiLeaks document. And so the judge had to force this witness for the prosecution to recant.

And this came on sentencing, when Chelsea Manning was there in sentencing. And so Ellsberg is going back and forth, and, as he says and I think this is a great context for it you know, this small fraction of people who the government is claiming to be murdered on both sides of this conflict, what theyre trying to say is that there were, some people, maybe a few people, who ultimately might have been killed by the disclosures of these WikiLeaks documents. But we cant lose perspective in talking about the carnage that has gone on. And in that respect, I can say, the Iraq War Logs revealed that 15,000 more people 15,000 more civilians were killed in that war zone than were previously known before those disclosures.

And so Ellsberg was trying to place it into the context of war that has gone on throughout the region for the last 20 years. He even spoke to the displacement of the 37 million people that has unfolded in the region, and saying he didnt actually believe that these government agencies truly care at all about these Middle Easterners, or the people in Afghanistan.

Because, in fact, and this is an important point, Julian Assange asked for help from the State Department and the Pentagon on the redactions. And they would not provide any assistance in removing the names or giving him any information that would help him understand whether someone would be put at risk. And weve had this corroborated by journalists who are working on the material. So Im not just trying to say this to be a booster of Assange. Weve heard evidence in this case of WikiLeaks actually trying to do good diligence with the material. And yet because they dont want Wikileaks to be treated as a journalist organization or a media organization, they would not do business basically.

Whats interesting is a lot of this hinges not on press freedom, but actually on human rights, because the United States takes a much more liberal view, so to speak, of what the state and what the prison system is allowed to do to the people who are in its charge. The rest of the kind of industrialized world does not treat prisoners the way that we do. And so the the Assange defense is saying that if you extradite Assange to the United States he will be locked in a hole, hell spend his life in isolation in a supermax, and eventually, probably in Colorado, where he will suffer the most kind of depraved state action that you can contemplate, short of ripping somebodys toenails out.

RG: And so what was the argument that was being made by the defense around the prison conditions in the United States?

KG: First off, we hear the argument that was made through an attorney named Lindsay Lewis in the past week, who represented Mustafa Kamel Mustafa, who is I think more commonly known to people as Abu Hamza, and he was accused of terrorism offenses. And he had a high-profile extradition case in the UK. And in fact, shes representing him when it comes to the very issues that Julian Assange could have, if he is brought to the U.S., put on trial, and sentenced to or placed under special administrative measures in Florence, Colorado at ADX Florence, this supermax prison.

And so she knows what Julian Assange will have to deal with. And she says that there were representations, and reference these representations that the warden who was there at the time made to these British courts about how someone who was in ill health, like Abu Hamza, even though he was accused of very serious terrorist offenses, even though there might have been evidence for him being involved in some terrible acts, he, himself had ill health and he has physical disabilities. And so he was unlikely to be at the supermax prison for more than a short period of time. And because he wouldnt be there for a lengthy indefinite period, it was not deemed by any of the courts that reviewed the case and also heard his appeals and this includes the European Court of Human Rights it was deemed that there was no reason to have any concern about him. He could be allowed to be brought to the U.S., because they would do a medical evaluation if he was in the supermax prison, and then they would probably determine that he should go to a medical center and not be held in solitary confinement at the supermax facility.

None of that played out. All the assurances that were made to the courts turned out not to be true. And he is still there. After his conviction in 2014, he has been in supermax under special administrative measures, which is a way of restricting your communication with the outside world, and hes been there for five years. And this is indefinite. And hes challenging his detention.

And so this was put forward as a clear example of what Julian Assange could expect. And I think its really fair to draw this comparison, because Ive been a bit baffled in following this, because every time theres a witness who speaks on the prison issues, and how he would be sentenced, weve had multiple attorneys from the United States, and we also have people with backgrounds in following prison issues, or we even had a former Warden named Maureen Baird, who testified during the fourth week. And when they talked about how Julian Assange would be designated a national security defendant, and the U.S. government, its intelligence agencies, that make determinations about authorizing SAMs, because SAMs have to be authorized by the attorney general, when they talk about why they would want to designate him for Sams during pre trial and also for post trial, the prosecutors have denied that they would treat them like this because theyre afraid he would further disclose classified information. They have denied that they would view him as a national security threat, who would not be permitted to speak to other prisoners, because they would be afraid that he would spread sensitive information that they do not want circulating.

This was a factor in Chelsea Mannings case. This is partially why she was held at Quantico Marine Brig in conditions of solitary confinement for a period of time, because while they said it was protective custody, there was also evidence, if you read between the lines, that made it very clear that they did not want her talking to other people who were held at the brig at Quantico about the information that she had disclosed to WikiLeaks, because it was classified information.

And so I think that theyre being deceitful. And I dont know if the judge can tell that theyre being deceitful, but we have this clear example. And what theyve been trying to show is that, you know, Julian Assange is likely to receive a lengthy sentence, because of how the charges could be stacked, because of how you could add enhancements to the charges, to the offenses, and that hes likely to receive a 20- to 30-year sentence. Hes a 50-year-old man, hes 49 years old right now, but by the time hes on trial, lets say its going to be one to two, or maybe three years from now, he would be in his 50s. If he was sentenced to 20 to 30 years, thats essentially a life sentence.

And wherever he goes, what were hearing is clear evidence that before the trial at the Alexandria Detention Center, he would be put in conditions of solitary confinement. Hes a high-profile defendant, so he would be treated like Paul Manafort and Maria Butina were treated. And then if hes convicted, he would be brought to a facility like ADX Florence, or I think that theres evidence that is persuasive that he could be brought to a communications management unit in Terre Haute, Indiana or in Marion, Illinois.

And Ill say in concluding that one of the rare questions that was asked of a witness by the judge, the judge doesnt ask witnesses many questions. One question she did have was why theres a difference between the UK and the U.S. in how we treat high-profile defendants. Because in the UK, Julian Assange has not been punished for the fact that there is a lot of publicity toward his case. However, in the U.S., its different. We know from whistleblower cases that people get punished. Anyone in prisons, or anyone in jail before trial, who has the ability to access media and defend themselves in the court of public opinion, is typically retaliated against by wardens and management of those facilities. And so she asked, Whats the difference?

And he said: You know, I dont really know what the difference is. This is Yancey Ellis, hes a public defender, now an attorney who works in the Eastern District of Virginia representing people in the Alexandria, Virginia area who have gone through that court system and who have been detained and held at the Alexandria Detention Center. And he said: I dont really know why theres a difference. I can just tell you that those types of defendants are treated in this manner, that they are kept in isolation, and treated that way by the detention center.

RG: Were gonna keep watching this. And Kevin Gosztola, thank you so much for your coverage of this important hearing. And thank you for joining us here on Deconstructed.

KG: Thank you.

[Musical interlude.]

RG: That was Kevin Gosztola of the outlet Shadow Proof. The issues he just described to us are not theoretical, and theyre not unique to Julian Assange. Retaliation against high-profile prisoners, and anybody who attempts to talk to the press is real.

Were joined next by somebody who knows that all too well. Dana Gottesfeld has been battling for years to bring attention to the case of her husband, Martin Gottesfeld, whos serving a sentence in a federal prison in Terre Haute Indiana, in a so-called communications management unit, or CMU, where his access to visitors and other inmates is severely restricted.

Dana thanks for joining us on Deconstructed.

Dana Gottesfeld: Hi Ryan. Thank you.

RG: So Dana, I know you havent been in communication with Marty for a few months now. But what was the latest that youve heard from him about what life is like in that CMU?

DG: It never ceases to disturb me. Ive definitely had a much different understanding of the criminal justice system now that Ive seen it up close. Some of the things that they do, they are just so unconstitutional. And theres so little accountability. It certainly doesnt feel like any America that I would recognize. Its upsetting.

But some of the things they do there are they block mail between clients and attorneys. Martys had mail that went out to his attorney that got stopped at the sorting facility in Vermont where his attorney is, and it never has left the facility. They read mail between attorneys and clients and between clients and the courts. Its a very dystopian place. They wont give out a list of written rules of what you can and cant do, but then theyll punish people afterwards and say, That wasnt allowed. And these are all things that have happened to Marty.

RG: Whats a typical day like for Marty?

DG: Well, anytime theres a COVID case, the entire facility gets locked down. So thats, I think, 23 hours-a-day lockdown. I think theres a usual amount of lockdown throughout the day anyways, but I imagine its not so good. I think he just sits in his cell and writes. Yeah.

RG: Has he had a cellmate the entire time or has he spent time in isolation as well?

RG: And I dont think he has a cellmate and he has spent time in the SHU which is the special housing unit or solitary there. Its probably one of the worst SHUs Ive heard of. And Martys been in probably more than six facilities in the U.S..

RG: What is it about the Indiana prison, their solitary, that makes it so much worse in your mind?

DG: Well, theres a huge rodent and cockroach infestation. Theres no desk to do any writing, so he has to bend over and do it over bed. They had a SWAT team go into his cell multiple times a day. Hes not leaving the cell, so its not like anything is changing, its just to, I dont know, throw him off, upset him.

They have him chained and shackled. He was on a hunger strike in the CMU and he would drink water, but they would make it too difficult for him to actually get the water because of his chains.

Theyre just so callous. And its not like its based in security for the facility or anything like that. Its just retaliation.

RG: Marty is an awfully strong person. Have you been able to sense what its done to him mental-health wise?

DG: Well, I havent spoken to him since August 31. But I can imagine hes probably pretty stressed and anxious. And I would like to see some kind of accountability.

RG: And where do you find that accountability? Thats what makes places like this so remarkable. Outside of the press, which hes effectively barred from communicating with, what can a family do, or what could an inmate do, to try to remedy the unconstitutional conditions theyre living in?

DG: In my opinion, thats one of the worst parts is how the prison has complete control over what a prisoner can do. Basically, they disabled the hotlines, so theres no way to report violations anonymously. They intercept [laughs] thats funny complaints to the Office of the Inspector General. The prison intercepts mail between him and the courts. They block mail to journalists. Its like theyre running some kind of show where they can do bad things, and then make sure no one can hear about it.

And then if you actually are successful, if you can get it to the OIG or the Regional Director of the Bureau of Prisons, they dont do anything. Theres people that should be removed from their position, or at least be held accountable to follow rules. One of the big things were seeing is made-up disciplinary actions. Like these are fraudulent, theyre fake on their head, just immediately looking at them. These are things that didnt happen he has written proof. And its so hard to get anything with that. Its like the truth doesnt matter. Its like living in an alternate reality or maybe its like living in a 2020 reality at this point.

RG: Right, right. Yeah, it certainly sounds that way.

DG: I think that the CMU and the prisons in the U.S. are especially bad for journalists. Its extremely hard to get writing done and prison staff are extra retaliatory towards people like that. I think if Assange comes to the U.S., he can expect at least as bad as Marty, and its extremely frightening.

RG: Well, well, Dana, thank you for taking some time and joining us here on Deconstructed. Please do send our best to Marty, if and when you hear from him next.

DG: Thanks Ryan.

See more here:
Why You Should Care About the Extradition of Julian Assange - The Intercept

WikiLeaks led the way for newsrooms to use encryption to protect sources says Italian journalist – ComputerWeekly.com

WikiLeaks pioneered the use of encryption and air gapped computers to protect sources and confidential documents later used in main stream news rooms, according to evidence by an Italian investigative journalist.

Stefania Maurizi said that the organisation had taken extensive measures to protect thousands of state department documents leaked by Chelsea Manning in 2010.

She gave written evidence during the four-week extradition trial of Julian Assange at the Old Bailey, which ended yesterday.

According to her evidence, US cables published by WikiLeaks showed that the US had successfully placed pressure on Italian politicians not to extradite and prosecute the CIA officers responsible for the kidnap and torture of an Egyptian cleric seized from the streets of Milan.

Assange is accused of offences under the Computer Fraud and Abuse Act and 17 counts under the Espionage Act after receiving and publishing thousands of classified documents from former US army intelligence analyst Chelsea Manning.

US prosecutors have alleged that Assange knowingly published thousands of unredacted state department documents which put US informants at risk.

Maurizi, a journalist with newspapers lEspresso and La Repubblica,worked as a media partner with WikiLeaks for over 9 months to analyse US State Department cables related to Italy and used local knowledge to redact the names of individuals who might be at risk if their names were disclosed.

Maurizi, who has a degree in maths and wrote a dissertation on cryptography, said that WikiLeaks had pioneered the use of encryption to protect journalistic sources.

Julian Assange and WikiLeaks were pioneering the use of encryption to protect journalistic sources and this was of great interest to me both as an investigative journalist and a mathematician, she said.

At the time no major newsroom was using cryptography to systematically protect sources, and it would be years before other newsrooms, such as the Guardian and the Washington Post introduced Cryptography.

WikiLeaks made original documents available on its web sites so that people could access the original documentation and check the accuracy of published media reports. Assange called it scientific journalism, said Maurizi.

The journalist worked with Assange on the Iraq War logs in 2010 and was given access to over 4,000 State Department cables in 2011.

I was given an encrypted USB stick and once I returned to Italy I was given a password that would then allow opening the file. Everything was done with the utmost responsibility and attention, she said.

Maurizi used an air-gapped computer, which she never left unattended, to analyse the cables, and adopted other security measures.

Even the work done by close colleagues on stories regarding the Italian Mafia requiring extreme caution and security never reached these levels, she said.

Maurizi said that she redacted any sensitive names - using 12 Xs, so that the length of the name did not provide any clue to the identity - before they were published by WikiLeaks.

The diplomatic cables shed light on extremely serious human rights violations including torture and kidnapping, said Maurizi.

They revealed that the US had put pressure on Italian politicians not to extradite US citizens and CIA agents held responsible for the kidnaping and extraordinary rendition of Abu Omar from the streets of Milan.

Omar was taken to Egypt in 2003 where he was held in cell, blindfolded and handcuffed and repeatedly tortured for 14 months, according to an investigation by Mother Jones.

Omar was sentenced in his absence to 6years onterrorism charges ina decision confirmed by the Italian Supreme Court in 2015.

Thanks to a series of blunders by the US agents, Italian prosecutors identified 26 US citizens, mostly CIA officers, responsible for the kidnapping.

They were tried in absentia and convicted by the Italian supreme court between 2012 and 2014 to sentences of between 6 and 9 years.

Under US pressure, successive Italian justice ministers refused to issue extradition requests to the US to put the suspects on trial in Italy, and several of the suspects received presidential pardons.

Without WikiLeaks publication of US diplomatic cables, it would have been impossible to acquire factual and solid evidence about the US pressures on the Italian politicians, said Maurizi.

Maurizi said that she learned that one of WikiLeaks media partners passwords had been compromised during a trip to visit Assange, who was then a guest at Ellingham Hall, a country house in Norfolk, in August 2011.

The password had been disclosed in a book on WikiLeaks, Inside Julian Assanges War on Secrecy written by Guardian journalists David Leigh and Luke Harding.

Later the German Newspaper Der Freitag published a story that did not reveal the password but made it possible for people to connect the dots.

There was an ever-widening awareness that the files, until then considered to be safely encrypted might nonetheless be public very soon, she said.

Copies of an encrypted file containing the unredacted State Department documents had been circulating on the internet.

Christian Grothoff, an expert in network security from the University of Applied Sciences in Bern, told the court on 21 September that the file was likely to have been distributed after people mirrored the contents of WikiLeaks following a denial of service attack.

Maurizi said, WikiLeaks was in the position of its own data having been irreversibly and repeatedly embedded in the internet and they could not undo what had happened.

She said that Assange was acutely troubled by the situation and made urgent attempts to inform the State Department that information was circulating out of control.

When WikiLeaks published the unredacted documents, following their publication on the US web site Cryptome, Maurizi contacted security expert Bruce Schneier.

According to extracts quoted in Maurizis evidence, Schneier said in an email that both parties made dumb mistakes. He said that If I were to assess the blame the Guardian made the worse mistake. Without the key no one would have been able to brute force the file. No one, probably not even aliens with a planet-sized computer.

A judge will rule whether the UK should grant the US request to extradite Assange on 4 January 2021.

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WikiLeaks led the way for newsrooms to use encryption to protect sources says Italian journalist - ComputerWeekly.com

4 Reasons Why Encryption Is a Must for Data Protection – CIOReview

FREMONT, CA:Data breaches are becoming more common in todays business world. Hackers know they can sell sensitive information on the dark web or use it for malicious purposes. However, encryption technology for data protection is available for data protection. It involves securing information with cryptography through a scrambled code. People with the key to decoding sensitive data can only read it. Here are some reasons for enterprises to depend on encryption technology.

Usage Across Variety of Devices

One of the top advantages of encryption technology is that enterprises can apply it to all or most of the tech devices they use. Depending on needs, providers offer full hard disk or file-based encryption. Since several possibilities exist for companies who want to encrypt their data, it is worth researching to see which methods are most appropriate for enterprises. Multi-device encryption is also becoming more essential among businesses.

Avoid Regulatory Fines

Depending on the given industry or the specific policies set forth by the companies, encryption technology for data protection may become mandatory rather than optional. In several industries that often business with sensitive information, regulatory fines are a genuine concern. Besides how these incidents cut into an organizations profits, a bad reputation could give customers second thoughts about doing business with enterprises that dont responsibly store data.

Help Protect Remote Workers

C-level executives believe that the danger of a breach is greater when employees work remotely. This is not surprising as many remote workers store sensitive data on their devices, and enterprises have little control over how this data is accessed and shared. For that, all confidential data should be encrypted, and remote workers should use a virtual private network (VPN) to stay protected from cyber criminals intercepting unsecured network connections and distributing malware.

Increase Consumer Trust

For most companies, encryption is not a mandatory regulatory requirement. However, enterprises may want to use encryption to gain trust from their customers. According to a recent survey, 53% of enterprises are concerned about online privacy. Given the erosion of trust that firms experience in recent years, advertising the fact that the business is conforming to data encryption standards could give it a competitive advantage.

See also:Top VPN Services

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4 Reasons Why Encryption Is a Must for Data Protection - CIOReview

Best Encryption Software in 2020 – Latest Quadrant Ranking Released by 360Quadrants – Yahoo Finance

TipRanks

Since 2019, the healthcare sector has been bracing for the wild ride that would be the election year. However, according to some Street pros, 2021 is looking a lot like 2009, and this could actually be a good thing for the space.[We] think 2021 will play out very similarly to 2009 for the health care sector. If in fact the political prediction markets are correct and Democrats seize control of the presidency and the U.S. Senate, the rhetoric on changes to health care policy exceeds the reality of what can be accomplished," UBS healthcare strategist Eric Potoker noted.Potoker points out that the 2009 passage of the Affordable Care Act (ACA) had a muted effect on the industry, with demand for products and services rising due to expanded health coverage. Healthcare stocks reaped the benefits of this between 2009 and 2015, and the space outperformed the rest of the market.To this end, Potoker believes 2021 will play out in a very similar way, and therefore, is pointing to the healthcare space as a must-watch area of the market.Using TipRanks database, we scanned the Street for compelling yet affordable plays within the healthcare sector. Locking in on three trading for less than $5 per share, the platform revealed that even with the risk involved, all three have scored overwhelmingly bullish analyst support, enough to earn a Strong Buy consensus rating. Whats more, each boasts a massive upside potential.Kintara Therapeutics (KTRA)Working to meet the needs of patients who are failing or resistant to current treatment regimens, Kintara Therapeutics focuses on developing cutting-edge cancer therapies. Based on its diverse oncology-focused pipeline and $1.40 share price, some members of the Street believe the share price reflects an attractive entry point.Aegis analyst Nathan Weinstein cites the company's two differentiated, late-stage oncology assets as the primary components of his bullish thesis. These candidates are VAL-083, a small molecule chemotherapeutic agent for the treatment of glioblastoma multiforme (GBM), a highly lethal brain cancer with a 95% five-year mortality rate, and REM-001, a phototherapy designed for the treatment of cutaneous metastatic breast cancer (CMBC).Looking at the former, Weinstein highlights the fact that VAL-083 affects DNA in a different way than the current standard of care, temozolomide (TMZ). We think VAL-083 could show relative benefit, particularly in MGMT-unmethylated patients. Two thirds of GBM patients have an unmethylated MGMT promoter, the analyst noted.The MGMT repair enzyme has been found to correct the damage to DNA caused by TMZ. However, patients with an unmethylated MGMT repair enzyme have a poor response to TMZ treatment, which bodes well for KTRA as its therapy has a different mechanism of action. In our view, data from the ongoing Phase 2 trials presented at AACR (June 2020) are encouraging regarding overall survival (OS) and progression free survival (PFS) data vs historical controls, Weinstein opined.As for REM-001, it has been evaluated in over 1,000 patients to-date, and thus has a well-characterized safety profile, in Weinsteins opinion. Additionally, in previous CMBC trials, the asset has demonstrated robust efficacy, including 80% complete response of evaluable lesions.All of the above prompted Weinstein to comment, We find the valuation of Kintara in the market to be compelling, as little value is being ascribed to the company, despite having two phase 3 ready oncology assets with sufficient funding in-place to reach multiple milestones ahead.To this end, Weinstein rates KTRA a Buy along with a $6 price target. This target conveys his confidence in KTRAs ability to climb 341% higher in the next year. (To watch Weinsteins track record, click here)Are other analysts in agreement? They are. Only Buy ratings, 3 to be exact, have been issued in the last three months. Therefore, the word on the Street is that KTRA is a Strong Buy. Given the $4.33 average price target, shares could soar 218% from current levels. (See KTRA stock analysis on TipRanks)DiaMedica Therapeutics (DMAC)Utilizing its cutting-edge technologies, DiaMedica Therapeutics develops novel recombinant proteins to treat kidney and neurological diseases. With a price tag of $4.20 per share and potential catalysts coming up, its no wonder this stock is on Wall Streets radar.Representing Craig-Hallum, analyst Alexander Nowak sees multiple value-creating catalysts on tap, noting that the company appears chronically undervalued. Looking ahead to Q4, DMAC will have a meeting with the FDA for DM199 in acute ischemic stroke (AIS), where break-through designation, Special Protocol Assessment (SPA), Phase 3 trial design and a Phase 3 study greenlight will be topics of discussion. DM199, DMACs lead candidate, is a recombinant form of the KLK1 protein (an endogenous serine protease produced in the kidneys, pancreas and salivary glands).According to Nowak, this Phase 3 study is the next major potential catalyst and could possibly lead to strategic partnership conversations. He added, We also think a SPA that confirms exclusion of mechanical thrombectomy and large vessel occlusion and mRS/NIHSS Excellent Outcome endpoints is a big win (basically means replicate the Phase 2 study in the intent to treat population).While the meeting will take place later than Nowak thought (he originally expected an August meeting), the delay is due to hiring an external consulting group to help with FDA communication, a valid and sensible reason for the pushback, in his opinion.On top of this, DM199 is being evaluated in chronic kidney disease (CKD). The Phase 2 trial enrollment was temporarily paused in Q2, but enrollment has been trending better. It should be noted that the delays have mostly been related to patients that were nervous about coming into the clinic for the initial setup during the COVID crisis. Bearing this in mind, the analyst expects the data readout to come in Q1 2021. Summing it all up, Nowak stated, We still view the Phase 2 CKD trial as the more significant, immediate value-creating opportunity, given the large market and recent industry successes (RETA). But we are more bullish than most investors on stroke too, as the only drug used is more than two decades old, no serious competitors are in the pipeline and approval (which could be done in only a few hundred patients) could lead to a very rapid uptake within 1-2 years.Everything that DMAC has going for it convinced Nowak to reiterate his Buy rating. Along with the call, he attached a $15 price target, suggesting 265% upside potential. (To watch Nowaks track record, click here)Overall, DMAC shares get a unanimous thumbs up from the analyst consensus, with 3 recent Buy reviews adding up to a Strong Buy rating. At $14.33, the average price target implies 248% upside potential from current levels. (See DMAC stock analysis on TipRanks)OPKO Health (OPK)Through its unique products, comprehensive diagnostics laboratories and robust research and development pipeline, OPKO Health wants to improve the lives of patients. OPKO shares have surged 162% this year, but at $3.86 apiece, several analysts believe this stock is still undervalued.Following the announcement that OPK had kicked off the Phase 2 REsCue study of Rayaldee for the treatment of mild-to-moderate COVID-19, 5-star analyst Edward Tenthoff, of Piper Sandler, points out that he has high hopes for the company. Rayaldee is currently approved for secondary hyperparathyroidism (SHPT) in stage 3-4 Chronic Kidney Disease (CKD), and is progressing through a Phase 2 study in dialysis patients.According to Tenthoff, many of the patients in the COVID study will have stage 3-4 CKD, where Rayaldee has demonstrated clinical benefit. On top of this, the analyst thinks boosting serum 25D may augment macrophage immunity by secreting potent antiviral proteins targeting.Reflecting another positive, service revenue of $251 million in Q2 2020 beat expectations as a result of the 2.2 million SARS-CoV-2 PCR and antibody tests performed at BioReference Labs in the quarter. Adding to the good news, OPK guided for 45,000-55,000 tests per day in Q3 2020 and service revenue of $325-350 million in the quarter. It should be noted that this includes the base diagnostic business, which is starting to bounce back. To this end, Tenthoff estimates service revenue could climb 53% higher to reach $1.1 billion this year.Tenthoff is also looking forward to the somatrogon, the companys treatment for pediatric growth hormone deficiency (GHD), regulatory filings. Its partner, Pfizer, plans to submit the BLA this fall, with U.S. approval and market launch potentially coming in 2H21. An open-label European study is expected to wrap up this quarter, and will enable an EMA filing in 2021. In addition, pivotal Phase 3 Japanese data in pediatric GHD patients could support a regulatory filing in the country in 1H21.Based on the therapys Phase 3 trial, in which it met the primary endpoint with height velocity, Tenthoff sees approval as being likely.In line with his optimistic approach, Tenthoff stays with the bulls. To this end, he keeps an Overweight (i.e Buy) rating and $10 price target on the stock. Investors could be pocketing a gain of 159%, should this target be met in the twelve months ahead. (To watch Tenthoffs track record, click here)All in all, other analysts echo Tenthoffs sentiment. 4 Buys and no Holds or Sells add up to a Strong Buy consensus rating. With an average price target of $8, the upside potential comes in at 107%. (See OPKO stock analysis on TipRanks)To find good ideas for healthcare stocks trading at attractive valuations, visit TipRanks Best Stocks to Buy, a newly launched tool that unites all of TipRanks equity insights.Disclaimer: The opinions expressed in this article are solely those of the featured analysts. The content is intended to be used for informational purposes only. It is very important to do your own analysis before making any investment.

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