Cybersecurity and AI

Machine Learning (ML) is a branch of Artificial Intelligence (AI) that refers to technologies that enable computers to learn and adapt through experience. It emulates human cognition i.e. learning based on experience and patterns, rather than by inference (cause and effect). Today, deep learning advancements in machine learning allow machines to teach themselves how to build models for pattern recognition (rather than relying on humans to build them).

The last five years have really seen a rise in AI and ML technologies for enterprises. Most of which can be attributed to advancements in computing power and the evolution of paradigms like distributed computing, big data and cloud computing.

Early commercial applications of ML were pioneered by technology titans like Google (in its search engine), Amazon (with its product recommendations) and Facebook (with its news feed). These businesses managed to build a veritable treasure trove of valuable behavioral data from hundreds of millions of users. In order to effectively collect, cleanse, organize and analyze their consumer data, these companies built scalable big data frameworks and applications, then open sourced them to the world. By opening access to these big data frameworks, they improved fast, scaled quickly and allowed businesses to derive more value from their data. Kris Lahiri, Co-founder, Chief Security Officer, Egnyte, is of the opinion that organizations are already beginning to use AI to bolster cybersecurity and offer more protections against sophisticated hackers. AI helps by automating complex processes for detecting attacks and reacting to breaches. These applications are becoming more and more sophisticated, as AI is deployed for security.

Data deception technology products can automatically detect, analyze, and defend against advanced attacks by proactively detecting and tricking attackers. So, when you combine very smart security personnel with adaptive technology that continues to change and become smarter over time, this provides a competitive edge to defenders that have primarily been absent from most cybersecurity technologies to date. Automation fuels industry growth. Vince Steckler, CEO Avast says “Cybersecurity is a good investment opportunity, because what investors may not realize, is that cybersecurity is something that constantly changes”.

On the other hand, AI can open vulnerabilities as well, particularly when it depends on interfaces within and across organizations that inadvertently create opportunities for access by "bad actors" or disreputable agents. Attackers are beginning to deploy AI too, enabling it to have the ability to make decisions that benefit attackers. Meaning they will gradually develop automated hacks that are able to study and learn about the systems they target and identify vulnerabilities, on the fly.

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