AI Combating Cyber Attacks

It is almost every other day that we hear, “We live in a digital world and our lives are getting more digital by each passing day”. And it is true. However, the digitisation of our lives have also opened doors for new kinds of threats — online threats or cyber attacks. 

As diamond cut diamond, now, newer technology is being employed to fight cyber attacks. There has been a rise of new intelligent systems for some time now. But when you talk of human-like intelligence and beyond, that is what we have been witnessing recently — the rise of AI/ML. 

In the technology industry for a considerable time, an observation emerges: the merging of technology has a transformative impact on lives. Two different technologies which are originally focused on two different objectives, so often come together and heavily impact how we live our lives.An anecdote comes to mind, highlighting how a technology initially designed for ergonomic relief in personal computer use, upon integration with mobile computing, gave birth to a new universe—the iPhone. The evolution is such that imagining a time without smartphones now seems unfathomable.

Something on a similar note is the idea of employing AI/ML to strengthen cybersecurity today and in the future. When we say Cybersecurity, it may sound like a single domain, but it is actually a very diverse world, just like a rainforest. Ensuring security in the digital world needs being vigilant at each step, from information generation, its transmission to its storage. And vigilance at every moment too. We need AI/ML to not only provide us the power but also the intelligence to do that. The ability of AI/ML to collect, process and analyze massive amounts of data to identify cybersecurity risks and design appropriate protection and mitigation tactics, makes it a remarkable tool for us to create a safe digital experience for all humans.

 But how exactly is that done, right? AI/ML today is really good at finding patterns and by that, it can detect unusual traffic on the network and understand user behavior to flag anomalies and raise suitable alarms. This helps in protecting us from the damage that cyber-attacks may cause by alerting us upfront. Our daily communication on the internet includes frequent sharing of files, be it pictures of our dear ones or the sharing of official documents. AI/ML offers us a brain that is always active and scans each file to detect any indicators of potential risk, which proves to be instrumental in avoiding malware and keeping our data to ourselves. AI/ML models can predict potential risks that a system or network is vulnerable to, from the historical data it has about it and/or the attacks that it has been subjected to. It is like AI/ML providing us a cheat sheet to keep threat actors away. Until now, we have looked at how AI/ML helps us improve cybersecurity by making us more immune to cyber attacks. But its application is not limited to that. AI/ML can also perform automated threat responses. The models can assign scores to events depending on the potential risks they carry and adjust the magnitude and swiftness of the response accordingly. 

Almost all of us have received that email that promises us a million dollars or a sports car as a lottery prize. Or maybe an alert about our social media account being deactivated until we acted quickly and clicked a button. A lot of systems get compromised when people interact with emails like these and without their knowledge, lose their credentials, money and much more. These are sugar-coated cyber-attacks. We may wonder about the application or advantage of AI/ML in this scenario. Well, ML algorithms can analyze email content, user behavior, and communication patterns to identify phishing attempts, oftentimes finding details that may escape the naked human eye, to protect users from falling victims to them. 

Authentication is another critical part of ensuring the security of information. AI/ML-enabled authentication systems can tweak the authentication requirements with the evolving risk landscape, making it harder for unauthorized users to gain access. A lot of us have been victims of identity theft and data stealing when a threat actor was able to exploit a vulnerable authentication mechanism. Such attacks, which include data exfiltration, are probably the closest to the skin of users because there is an immediate loss at the user’s end. AI/ML can improve our deterrence to such attacks by employing it’s pattern recognition capabilities and detecting abnormal data transfer patterns within a network, identifying potential data exfiltration attempts.

Its ability to continue to learn with tonnes of data coming in every moment, improving its understanding of vulnerabilities, cyber-attacks and mitigation techniques, makes AI/ML as a remarkable tool in the hands of cybersecurity professionals. 

Some points should be addressed in conclusion. The landscape of cybersecurity is very dynamic with threat actors continuing to use new techniques and technologies to compromise our privacy. We need a system that matches their pace, and we have that in AI/ML. It can help us enhance cybersecurity across the stages that I mentioned earlier, i.e., generation, transmission, and storage. New frontiers in the domain of utilizing AI/ML for cybersecurity are continually being explored. As we continue to improve upon existing ML models and develop new ones, cybersecurity is going to be a really lively place.

-By Amit Singh- Founder and CEO of TelioLabs