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New PDF release: [Article] Neural Solutions for Information Security

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Extra info for [Article] Neural Solutions for Information Security

Sample text

To achieve reliable and efficient malware detection, we need to design our signature structure to meet four requirements in below. Basically, signatures should contain (1) behavioral semantics for basic detection capability. And, if a target application identified as a variant of known malware, then it could be (2) identifiable as a member of certain malware family. Also, to 20 S. Lee, J. Lee, and H. Lee overcome the pitfalls of legacy signature-based approach, our signature should be (3) reliable against different evasion techniques while maintaining (4) the efficiency as a signature-based approach.

ACM (2011) 16. : Android’s popularity makes it open target for malware, says study. uk Abstract. Many existing research efforts in the field of malware proliferation aim at modelling and analysing its spread dynamics. Many malware dissemination models are based on the characteristics of biological disease spread in human populations. In this work, we utilise game theory in order to extend two very commonly used malware spread models (SIS and SIR) by incorporating defence strategies against malware proliferation.

By adopting the exploits, application is being able to perform kernel-level control of the device without any user notification. The most risky and widespread malwares such as DroidDream and DroidKungfu initially contain exploits to perform high-risk malicious activities surreptitiously. Since the exploitation is the most serious threat for users, we detect known privilege escalation exploits that either contained in known malwares or be searched on internet forums. – Remote Control Over 90% of currently reported Android malwares have remote control capability.

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[Article] Neural Solutions for Information Security


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