How AI Cybersecurity Is Using Machine Learning to Launch Attacks
As business leaders increasingly embrace AI, cybersecurity solutions powered by machine learning are emerging. This can help improve security posture, minimize breaches and prioritize risk, and accelerate incident response. But the technology is also being used to launch attacks, as cyber criminals discover ways to leverage the technology to develop more sophisticated attacks.
The best way to fight the constantly changing range of new threats is for protection systems to proactively detect them, rather than waiting for an attack to occur and then reacting. This requires a system that can quickly analyze huge data sets, looking for all manner of behaviors, including malware, phishing and “cryptojacking,” where infected machines are directed to mine cryptocurrency for hackers.
This is the role that AI cybersecurity plays, as it examines huge data sets and looks for all types of suspicious behavior to flag a threat. It can run across all the endpoints in a network or cloud and even look at devices connected to them, such as IoT devices, to check for suspicious activity. It can also operate at the edge on an endpoint, where it could look for patterns of phishing and ransomware, for example.
Companies such as Darktrace and Falcon are using AI to defend against the latest threats, such as WannaCry, by analyzing all the data that moves between computers, clouds and IoT. It can also spot anomalies that would have gone unnoticed by human users, thereby mitigating insider threats — which remain a major problem for businesses of all sizes.