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Auto-Sign: an automatic signature generator for high-speed malware filtering devices
Authors:Gil Tahan  Chanan Glezer  Yuval Elovici  Lior Rokach
Affiliation:(1) Department of Computer Science, The University of Texas at Dallas, 2700 Waterview Pkwy, #5116, Richardson, TX 75080, USA;(2) Department of Computer Science, The University of Texas at Dallas, Box 830688, EC 31, Richardson, TX 75083-0688, USA
Abstract:This research proposes a novel automatic method (termed Auto-Sign) for extracting unique signatures of malware executables to be used by high-speed malware filtering devices based on deep-packet inspection and operating in real-time. Contrary to extant string and token-based signature generation methods, we implemented Auto-Sign an automatic signature generation method that can be used on large-size malware by disregarding signature candidates which appear in benign executables. Results from experimental evaluation of the proposed method suggest that picking a collection of executables which closely represents commonly used code, plays a key role in achieving highly specific signatures which yield low false positives.
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