Machine Learning In Security: Seeing the Nth Dimension in Signatures

How adding “supervised” machine learning to the development of n-dimensional signature engines is moving the detection odds back to the defender. Second in a series of two articles about the history of signature-based detections and how the methodology has evolved to identify different types of cybersecurity threats. Many security vendors are now applying increasingly sophisticated machine learning elements into their cloud-based analysis and classification systems, and into their products. All of these techniques have already proven their value in Internet search, targeted advertising and social networking business arenas. For example, supervised learning models lie at the heart of ensuring that the best and most applicable results are returned when searching for the phrase “never going to give you up.” This is why signatures are still so important – not as…


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