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Proceedings Paper

Using qualia and novel representations in malware detection
Author(s): Bobby Birrer; Richard A. Raines; Rusty O. Baldwin; Mark E. Oxley; Steven K. Rogers
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Paper Abstract

Detecting network intruders and malicious software is a significant problem for network administrators and security experts. New threats are emerging at an increasing rate, and current signature and statistics-based techniques are failing to keep pace. Intelligent systems that can adapt to new threats are needed to mitigate these new strains of malware as they are released. This research develops a system that uses contextual relationships and information across different layers of abstraction to detect malware based on its qualia, or essence. By looking for the underlying concepts that make a piece of software malicious, this system avoids the pitfalls of static solutions that focus on predefined signatures or anomaly thresholds. If successful, this type of qualia-based system would provide a framework for developing intelligent classification and decision-making systems for any number of application areas.

Paper Details

Date Published: 20 May 2009
PDF: 9 pages
Proc. SPIE 7352, Intelligent Sensing, Situation Management, Impact Assessment, and Cyber-Sensing, 73520W (20 May 2009); doi: 10.1117/12.821082
Show Author Affiliations
Bobby Birrer, Air Force Institute of Technology (United States)
Richard A. Raines, Air Force Institute of Technology (United States)
Rusty O. Baldwin, Air Force Institute of Technology (United States)
Mark E. Oxley, Air Force Institute of Technology (United States)
Steven K. Rogers, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 7352:
Intelligent Sensing, Situation Management, Impact Assessment, and Cyber-Sensing
Stephen Mott; John F. Buford; Gabriel Jakobson, Editor(s)

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