Fighting malware is a modern arms race. Not only has malware evolved to be more evasive and harder to detect, but their vast numbers make it even more difficult to handle. As a result, detecting a malware has become a big data problem which requires the help of self-learning machines to scale the knowledge of analysts, handle the complexity beyond human capabilities, and improve the accuracy of threat detection.
There are number of approaches to this problem; choosing the right algorithm to serve the security engine’s purpose is not an easy task. In this article, we will refer to machine learning (ML) as an application of artificial intelligence (AI) where computers learn without being explicitly programmed.