Dr. Alexander Adam shares more insights on how deepfakes can be counteracted with the help of AI. Machine learning algorithms are great at recognising patterns in large amounts of data. ML can provide a way to detect fake audio from real audio by using classification techniques that work by showing an algorithm large amounts of deepfake and real audio and teaching it to distinguish the difference in the frequency composition between the two.

For example, by using image classification on the audio spectrograms you can teach an ML model to spot the difference. However, as far as I am aware no out-of-the-box solution exists yet.

Adam continues: In part, this may be because audio deepfake hasnt been regarded as being as much of a threat as video deepfake. Audio deepfake are not pitch perfect and you should be able to tell the difference if its tailored to a specific person that you know.

That said, interference across phone lines or staging general outside background noise could probably be used to mask a lot of this. And as there has been so much high profile media attention on deepfake videos, the public is perhaps less aware of the potential risks of audio deepfake. So, if you have a reason to be suspicious, you should always validate its who you think it might be.

How is the future shaping up in this regard? We expect that the creation and use of audio deepfake for malicious purposes will increase in the coming years and become more sophisticated.

This is because there is a better understanding of machine learning models and how to transfer what was used on one model to another person and train it quickly. But, its worth noting that as the generation of deepfake content gets better, typically so do the detection methods, concludes Dr. Alexander Adam.

Modex BCDB, a new take on blockchain technology

Currently, the majority of blockchain solutions present on the market are oriented towards blockchain as a service, limiting themselves to a rigid view and application of the technology. A company or the CTO (Chief Technology Officer) of a company can come to the realization, after a bit of study that their business can solve several issues and streamline back-end processes by implementing blockchain.

The problem is that in order for a company to implement blockchain technology only through its own tech team, they need to invest a significant amount of time and resources to study what type of blockchain is most suited for their needs, and commence a lengthy process of learning the development specificity of the respective blockchain, as well as scouting for developers proficient in the technology.

Modex BCDB is a new take on blockchain technology which removes the need to invest resources in blockchain training and facilitates fast adoption of the technology in businesses. The solution proposed by Modex is a middleware that fuses a blockchain with a database to create a structure which is easy to use and understand by developers with no prior knowledge in blockchain development.

As a result, any developer who knows to work with a database system can operate with our solution, without needing to change their programming style or learn blockchain. Through our blockchain component, Modex BCDB is able to transform with minimal changes any type of database into a decentralized database which holds the same valuable characteristics inherent to blockchain technology: transparency, increased security, data immutability, and integrity.

Modex BCDB doesnt work by deleting the existing database or data entries. The database is maintained intact throughout the process, data integrity is ensured by calculating the metadata of the records and storing it on the blockchain.

The system does not restrict access to the blockchain or to the database, so when a developer needs to make a reporting or ETL transformations, they can perform warehouse analytics by accessing the database directly. This is because Modex BCDB has been purposely designed to be agnostic. With our solution, clients are able to set up a network, regardless of the type of database employed. In a consortium, each company can maintain what type of database they prefer and connect them through a blockchain-powered network to ensure cohesion while protecting corporate interests.

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Using the power of blockchain to combat deepfake videos - Open Democracy