How AI and ML in the networking domain strengthens security – CISO MAG

In 2004, a few unmanned vehicles showed up at the starting gate of the lengthy course across the Mojave Desert this was the inaugural DARPA Grand Challenge. It signified the beginning of the technological race to develop a practical self-driving car, which sparked a global movement that continues even today.

The networking community too embarked on a similar journey to provide production-ready, economically feasible, Self-Driving Networks. Self-Driving Networks are autonomous networks that use Artificial Intelligence (AI) and Machine Learning (ML) to program independently and carry out prescribed intentions while eliminating complex programming and management tasks required today to run the networks. In view of this, the proliferation of data breaches and cyberattacks in todays networking environment has also increased, leading to extensive repercussions across businesses. As such, ML-based security solutions have become a major cybersecurity investment for organizations today.

By Rohit Sawhney Systems Engineering Manager at Juniper Networks India

Many experts believe that AI and ML will dominate cybersecurity in the future. Last year, at the Gartner IT Symposium/Xpo, analysts discussed how these two technologies will augment human decision-making, emotions, and relationships.

Rapid technological advances are enabling AI to disrupt the networking industry with new insights and automation. AI in the networking domain will be able to reduce IT costs and offer the best possible user experience. Not only will AI be able to reduce IT costs, but it will also bring in more productivity and efficiency in networking. Together, machine learning and AI could be key enablers, helping to reduce human effort and make cybersecurity faster, more consistent and accurate.

In fact, many Enterprises are already making greater investments to integrate solutions with machine learning algorithms into their existing security infrastructure. While traditional antivirus programs are still widely used to detect and neutralize threats, they do not have the capability to detect and mitigate sophisticated threats. ML-based security solutions like the Juniper ATP can help monitor potential threats in the network through threat intelligence features allowing IT security teams to detect any suspicious activity before the attack occurs.

AI comes to the rescue as it reduces the number of monotonous tasks that take up an engineers time, while ensuring they are always completed accurately, regardless of frequency and quantity. This allows engineers to focus on other business strategic tasks while maintaining network health and safety.

In a recent survey conducted by KPMG for its report, Living in an AI World 2020, analysts found that 92% of respondents agree that leveraging spectrum of AI technologies will make their companies run more efficiently. However, in the networking domain, IT simply cant meet the needs of todays stringent network requirements, without a robust AI strategy. The following are some technology elements that an AI strategy should include:

ML a subset of AI, is a prerequisite for any successful deployment of AI technologies. ML uses algorithms to parse data, learn from it, and determines or predicts without requiring explicit instructions. With that said, AI/ML can be leveraged for the following tasks in the networking domain:

About the Author

Rohit Sawhney is a Systems Engineering Manager at Juniper Networks India. He leads the team of Technical Consultants supporting Junipers North/East India & SAARC business. Prior to joining Juniper Networks, he has worked with IBM India and has industry experience of over 20 years. Rohit is a certified by Juniper Networks, Cisco and VMWare. He holds a masters degree in Computer Application from Sikkim Manipal University of Health, Medical and Technological Sciences and a Bachelors of Science in Electronics from Delhi University.

Disclaimer

CISO MAG did not evaluate/test the products mentioned in this article, nor does it endorse any of the claims made by the writer. The facts, opinions, and language in the article do not reflect the views of CISO MAG and CISO MAG does not assume any responsibility or liability for the same. CISO MAG does not guarantee the satisfactory performance of the products mentioned in this article.

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How AI and ML in the networking domain strengthens security - CISO MAG