Kaspersky deepens security offering through machine learning

Kaspersky Lab has used machine learning to strengthen its security portfolio with the introduction of an algorithm to detect groups of noxious files. The vendor patented a technology that allows for effective false-positive testing of heuristic signatures describing groups of similar malicious files. This patent is the latest addition to the company’s arsenal and is said to allow for reliable automation of a large proportion of routine virus analysis tasks. The detection rules, automatically created by processing limited amounts of newly discovered malicious files, describe groups of malicious objects as combinations of various characteristics. These characteristics include, sequences of system calls and events that are common for malicious objects and uncommon for whitelisted files. Kaspersky Lab director anti-malware research, Timur Biyachuev, said, as the amount of malicious files which the…

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