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• W220179937 abstract "Today’s networks and their users are under attack from an ever-expanding universe of threats and malware. Malware are malicious software codes that typically damage or disable, take control of, or steal information from a computer system. Malware broadly includes botnets, viruses, worms, Trojan horses, logic bombs, rootkits, boot kits, backdoors, spyware, adware, and other types of threats. The ever increasing danger of the future threat is its ability to evolve for avoiding system defenses. Future threats will be using machine learning to outsmart the defenses. Defense techniques will in turn learn new attackers tricks to defend against. Therefore the future of cybersecurity is a warfare of machine learning techniques. The more capable machine learning technique will win." @default.
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• W220179937 date "2014-01-01" @default.
• W220179937 modified "2023-09-23" @default.
• W220179937 title "Dynamic Logic Machine Learning for Cybersecurity" @default.
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• W220179937 doi "https://doi.org/10.1007/978-3-319-10374-7_6" @default.
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