Improving self defense by learning from limited experience

Authors:
Karen Z. Haigh;Steven A. Harp
Affiliations:
BBN Technologies, Cambridge, MA;Adventium Labs, Minneapolis, MN
Venue:
Proceedings of the 4th annual workshop on Cyber security and information intelligence research: developing strategies to meet the cyber security and information intelligence challenges ahead
Year:
2008

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Abstract

Prevalence of new attacks or attack variants presents an interesting challenge for autonomic cyber-defense: how does the autonomic defense mechanism learn from previous failures, acquiring immunity with experience, and do so as rapidly as possible. In the limiting case, only a single a single observed failure may be available for learning.