How AI/ML Can Thwart DDoS Attacks

After early excitement about artificial intelligence (AI) in the late 1980s and early 1990s, followed by a couple of "AI winters" -- periods of reduced funding, interest and even disillusionment -- we now again see great enthusiasm about all things related to AI and machine learning (ML). It is no wonder that AI/ML is also being considered for network security, including distributed denial-of-service (DDoS) protection. It's not that AI/ML algorithms have changed so radically -- but they have matured. In network security, like in many other fields, the abundance of data and greater-than-ever processing power makes it feasible to implement new AI/ML algorithms in silicon or in the cloud, allowing us to teach machines to be more accurate and faster than humans are. With DDoS security, the problem is distinguishing "good" from "bad" traffic and minimizing the mitigative actions to reduce the effect on "good" traffic.