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Selected Works of Mark Stamp
Contribution to Book
Exploring Hidden Markov Models for Virus Analysis: A Semantic Approach
2013 46th Hawaii International Conference on System Sciences (2013)
  • Thomas H. Austin, University of California, Santa Cruz
  • Eric Filiol, École supérieure d'informatique, électronique, automatique (ESIEA)
  • Sébastien Josse, École supérieure d'informatique, électronique, automatique (ESIEA)
  • Mark Stamp, San Jose State University
Link
Abstract
Recent work has presented hidden Markov models (HMMs) as a compelling option for virus identification. However, to date little research has been done to identify the meaning of these hidden states. In this paper, we examine HMMs for four different compilers, hand-written assembly code, three virus construction kits, and a metamorphic virus in order to note similarities and differences in the hidden states of the HMMs. Furthermore, we develop the dueling HMM Strategy, which leverages our knowledge about different compilers for more precise identification. We hope that this approach will allow for the development of better virus detection tools based on HMMs.
Keywords
  • virus construction kits,
  • malware,
  • hidden Markov model,
  • metamorphic malware
Disciplines
Publication Date
March 18, 2013
Publisher
IEEE
ISBN
978-1-4673-5933-7
DOI
10.1109/HICSS.2013.217
Publisher Statement
SJSU users: use the following link to log in and access the article via SJSU databases.
Citation Information
Thomas H. Austin, Eric Filiol, Sébastien Josse and Mark Stamp. "Exploring Hidden Markov Models for Virus Analysis: A Semantic Approach" 2013 46th Hawaii International Conference on System Sciences (2013) p. 5039 - 5048
Available at: http://works.bepress.com/mark_stamp/69/