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Proceedings Paper

Neuromorphic computing applications for network intrusion detection systems
Author(s): Raymond C. Garcia; Robinson E. Pino
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Paper Abstract

What is presented here is a sequence of evolving concepts for network intrusion detection. These concepts start with neuromorphic structures for XOR-based signature matching and conclude with computationally based network intrusion detection system with an autonomous structuring algorithm. There is evidence that neuromorphic computation for network intrusion detection is fractal in nature under certain conditions. Specifically, the neural structure can take fractal form when simple neural structuring is autonomous. A neural structure is fractal by definition when its fractal dimension exceeds the synaptic matrix dimension. The authors introduce the use of fractal dimension of the neuromorphic structure as a factor in the autonomous restructuring feedback loop.

Paper Details

Date Published: 22 May 2014
PDF: 8 pages
Proc. SPIE 9119, Machine Intelligence and Bio-inspired Computation: Theory and Applications VIII, 91190F (22 May 2014); doi: 10.1117/12.2052394
Show Author Affiliations
Raymond C. Garcia, ICF International (United States)
U.S. Army Research Lab. (United States)
Robinson E. Pino, ICF International (United States)


Published in SPIE Proceedings Vol. 9119:
Machine Intelligence and Bio-inspired Computation: Theory and Applications VIII
Misty Blowers; Jonathan Williams, Editor(s)

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