With cyber attacks on the rise, a new and more sophisticated threat is targeting our organisations, and it is undoubtedly much harder to detect
2022 will undoubtedly be another year of ransomware and cyber attacks. There looks to be no sign of it slowing down and no sign of threat actors taking a break. With attackers continuing to advance their skillsets, organisations must rise to the new and evolving challenges they bring. This includes recognising and detecting against the use of a relatively new attack vector called adversarial AI.
AI is one of the most advanced and rapidly fast-paced technologies of today. Most of the use cases we hear about is how organisations are using machine learning (ML), a subset of AI, to defend themselves against hackers. However, AI is now being used by bad actors to target organisations in order to launch cyber attacks and spread malware.
What exactly is Adversarial AI?
Adversarial AI manipulates the analytic and decision-making powers of AI and ML to develop cyber attacks in ways that were previously impossible by using ML tools to attack other ML tools. It exploits weaknesses in an organisation’s network to fool their systems into thinking the incoming attacks are harmless, and therefore granting free access and movement virtually undetected. The result is that malicious data sets are reclassified as benign and vice versa, allowing cyber criminals to send malicious programs into a business environment without the ML based security solutions flagging them as dangerous.
It is a highly sophisticated attack method, and one cyber criminals are undoubtedly already using stealthily to target organisations. Due to the complexity of the attack, once the SOC team have identified a potential issue, it is often already too late. The extra dwell time this attack gives to the threat actors, the more opportunity they have to move throughout the network, inflicting more and more damage as they go.
Prevention is key
Adversarial AI will only increase in the years to come, and organisations mustn’t be naïve to the genuine threat this attack can have on them as a business. For too long there has been a focus on what to do once your business has been hit. Wouldn’t it be better to be able to predict and prevent attacks before they enter and inflict damage on the network?
The ability to stop a hacker before they’ve had a chance to wreak havoc is no longer a pipe dream. It can be done using Deep Learning (DL) techniques, with this highly sophisticated approach creating neural networks, which mimic the human brain. As such, it can identify more complex, high-dimensional patterns and be more resilient, unlike the traditional machine learning. This allows it to counteract adversarial AI by outpacing the attacks and resisting attempts to change the model’s labelling.
More and more sophisticated threats will be used by cyber criminals trying to stay one step ahead of authorities and government agencies that are putting pressure on them. We therefore need to make 2022 a year of cyber change. The only way organisations can do this is if they look toward genuinely innovative solutions that focus on prevention and not on mitigation, detection, and response. We all need to level-up and not only meet, but surpass the techniques being used by our cyber adversaries.
BROOKS WALLACE | Technology Magazine
