Free Using Sequence Analysis to Perform Application-Based Anomaly Detection within an Artificial Immune System Framework
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Published on: 2012-10-17
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Original language: English
The Air Force and other Department of Defense (DoD) computer systems typically rely on traditional signature-based network IDSs to detect various types of attempted or successful attacks. Signature-based methods are limited to detecting known attacks or similar variants; anomaly-based systems, by contrast, alert on behaviors previously unseen. The development of an effective anomaly-detecting, application-based IDS would increase the Air Force's ability to ward off attacks that are not detected by signature-based network IDSs, thus strengthening the layered defenses necessary to acquire and maintain safe, secure communication capability. This system follows the Artificial Immune System (AIS) framework, which relies on a sense of "self," or normal system states to determine potentially dangerous abnormalities ("non-self"). Jianchun Li University of Technology Sydney A new encoding scheme is presented for a fuzzy-based nonlinear system identification methodology using the subtractive Fuzzy C-Mean clustering and a modified version ... ICEIS 2007 International Conference on Enterprise ... International Conference on Enterprise Information Systems Main Topic Areas: Databases and Information Systems Integration Artificial Intelligence and Decision ...
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