Feature set selection in data mining techniques for unknown virus detection: a comparison study

Authors:
Jianyong Dai;Ratan Guha;Joohan Lee
Affiliations:
University of Central Florida, Orlando, Florida;University of Central Florida, Orlando, Florida;Tradeworx Inc., Red Bank, NJ
Venue:
Proceedings of the 5th Annual Workshop on Cyber Security and Information Intelligence Research: Cyber Security and Information Intelligence Challenges and Strategies
Year:
2009

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Abstract

Detecting unknown viruses is a challenging research topic. Data mining approaches have been used to detect unknown viruses. The key to data mining lies on the feature set to be used. There are several different approaches have been tried before, simple heuristics, static features and dynamic features. In this paper, we present several different data mining approaches and compare the result of these approaches.