NDLI: Autonomic Security and Self-Protection based on Feature-Recognition with Virtual Neurons

Content Provider	IEEE Xplore Digital Library
Author	Yuan-Shun Dai Hinchey, M. Mingrui Qi Xukai Zou
Copyright Year	2006
Description	Author affiliation: Dept. of Comput. & Inf. Sci., Indiana Univ.-Purdue Univ., Indianapolis, IN (Yuan-Shun Dai)
Abstract	The Internet and networks are not security-oriented by design so that myriad problems are compromising today's computer systems. This paper presented an autonomic security mechanism based on the virtual neurons and feature recognition. A prototype model of the virtual neuron is designed and the distributed virtual neurons are organized in a compound peer-to-peer and hierarchical structure. Then, the autonomic security mechanism is implemented via features recognized by the distributed virtual neurons. The paper presented how the feature recognition and virtual neurons work to automatically detect various security problems that are currently hard to defend against, including eavesdropping, replay, masquerading, spoofing, and DoS. A simulation system was developed and different cases were studied
Starting Page	227
Ending Page	234
File Size	299194
Page Count	8
File Format	PDF
ISBN	0769525393
DOI	10.1109/DASC.2006.24
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-09-29
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Authorization Information science Neurons Autonomic nervous system Authentication Biology computing Control systems Computer networks Security Protection
Content Type	Text
Resource Type	Article

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