Titlebook: Recent Advances in Intrusion Detection; 12th International S Engin Kirda,Somesh Jha,Davide Balzarotti Conference proceedings 2009 Springer-

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Automatic Software Instrumentation for the Detection of Non-control-data Attackstem calls depend on and which constraints these sets must verify at runtime. We have implemented our approach using a static analysis framework called . and we present the results of experimentations on a vulnerable version of ..

Rustproof

0302-9743 Intrusion Detection systems (RAID 2009),which took place in Saint-Malo,France, during September 23–25. As in the past, the symposium brought together leading - searchers and practitioners from academia, government, and industry to discuss intrusion detection research and practice. There were six mai

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Malware Behavioral Detection by Attribute-Automata Using Abstraction from Platform and Languageto define a generic approach for behavioral detection based on two layers respectively responsible for abstraction and detection. The abstraction layer is specific to a platform and a language. It interprets the collected instructions, API calls and arguments and classifies these operations, as well

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Automatic Generation of String Signatures for Malware Detectionsizes. One solution to this problem is to use ., each of which is a contiguous byte sequence that potentially can match many variants of a malware family. However, it is not clear how to automatically generate these string signatures with a sufficiently low false positive rate. Hancock is the first

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PE-Miner: Mining Structural Information to Detect Malicious Executables in RealtimeE) to detect zero-day (i.e. previously unknown) malware. The distinguishing features are extracted using the structural information standardized by the Microsoft Windows operating system for executables, DLLs and object files. We follow a threefold research methodology: (1) identify a set of structu

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