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Using Sequence Analysis To Perform Application-Based Anomaly Detection Within An Artificial Immune System Framework, Larissa A. O'Brien
Using Sequence Analysis To Perform Application-Based Anomaly Detection Within An Artificial Immune System Framework, Larissa A. O'Brien
Theses and Dissertations
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 …
An Artificial Immune System Strategy For Robust Chemical Spectra Classification Via Distributed Heterogeneous Sensors, Mark A. Esslinger
An Artificial Immune System Strategy For Robust Chemical Spectra Classification Via Distributed Heterogeneous Sensors, Mark A. Esslinger
Theses and Dissertations
The timely detection and classification of chemical and biological agents in a wartime environment is a critical component of force protection in hostile areas. Moreover, the possibility of toxic agent use in heavily populated civilian areas has risen dramatically in recent months. This thesis effort proposes a strategy for identifying such agents vis distributed sensors in an Artificial Immune System (AIS) network. The system may be used to complement "electronic" nose ("E-nose") research being conducted in part by the Air Force Research Laboratory Sensors Directorate. In addition, the proposed strategy may facilitate fulfillment of a recent mandate by the President …