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Cyber Security: Why Machine Learning is Not Enough

Currently, there is a lot of talk about new analytical approaches in the field of cyber security. Anomaly detection and behavioral analytics are some of the overarching trends along with RTSI (Real Time Security Intelligence), which combines advanced analytical approaches with established concepts such as SIEM (Security Information and Event Management). Behind all these changes and other new concepts, we find a number of buzzwords such as pattern-matching algorithms, predictive analytics, or machine learning. Aside from the fact that such terms frequently aren’t used correctly and precisely, some of the concepts have limitations by design, e.g. machine learning. Machine learning implies that the “machine” (a piece of software) is able to “learn”. In fact this means that the machine is able to improve its results over time by analyzing the…

Link to Full Article: Cyber Security: Why Machine Learning is Not Enough