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Neural networks for computer virus recognition

Tesauro, G.J., Kephart, J.O. and Sorkin, Gregory B. (1996) Neural networks for computer virus recognition. IEEE Expert , 11 (4). pp. 5-6. ISSN 0885-9000

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Abstract

We have developed a neural network for generic detection of a particular class of computer viruses-the so called boot sector viruses that infect the boot sector of a floppy disk or a hard drive. This is an important and relatively tractable subproblem of generic virus detection. Only about 5% of all known viruses are boot sector viruses, yet they account for nearly 90% of all virus incidents. We have successfully deployed our neural network as a commercial product, distributing it to millions of PC users worldwide as part of the IBM AntiVirus software package. We faced several challenges in taking our neural network from a research idea to a commercial product. These included designing an appropriate input representation scheme; dealing with the scarcity of available training data; finding an appropriate trade off point between false positives and false negatives to conform to user expectations; and making the software conform to strict constraints on memory and speed of computation needed to run on PCs. The article discusses our methods for handling these challenges.

Item Type: Article
Official URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?pun...
Additional Information: © 1998 IEEE Computer Society
Library of Congress subject classification: Q Science > QA Mathematics > QA76 Computer software
Sets: Research centres and groups > Management Science Group
Departments > Management
Rights: http://www.lse.ac.uk/library/usingTheLibrary/academicSupport/OA/depositYourResearch.aspx
Date Deposited: 13 Apr 2011 15:02
URL: http://eprints.lse.ac.uk/35550/

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