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10.1109/NCA.2009.14guideproceedingsArticle/Chapter ViewAbstractPublication PagesConference Proceedingsacm-pubtype
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An Experimental Study of Diversity with Off-the-Shelf AntiVirus Engines

Published: 09 July 2009 Publication History

Abstract

Fault tolerance in the form of diverse redundancy is well known to improve the detection rates for both malicious and non-malicious failures. What is of interest to designers of security protection systems are the actual gains in detection rates that they may give. In this paper we provide exploratory analysis of the potential gains in detection capability from using diverse AntiVirus products for the detection of self-propagating malware. The analysis is based on 1599 malware samples collected by the operation of a distributed honeypot deployment over a period of 178 days. We sent these samples to the signature engines of 32 different AntiVirus products taking advantage of the VirusTotal service. The resulting dataset allowed us to perform analysis of the effects of diversity on the detection capability of these components as well as how their detection capability evolves in time.

Cited By

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  • (2014)Antivirus securitySoftware—Practice & Experience10.1002/spe.219744:10(1201-1222)Online publication date: 1-Oct-2014
  • (2013)Using agent technologies to correlate and compare anti-malware softwareProceedings of the 2nd annual conference on Research in information technology10.1145/2512209.2512212(17-22)Online publication date: 1-Oct-2013
  • (2013)A clinical study of risk factors related to malware infectionsProceedings of the 2013 ACM SIGSAC conference on Computer & communications security10.1145/2508859.2516747(97-108)Online publication date: 4-Nov-2013
  • Show More Cited By

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Published In

cover image Guide Proceedings
NCA '09: Proceedings of the 2009 Eighth IEEE International Symposium on Network Computing and Applications
July 2009
333 pages
ISBN:9780769536989

Publisher

IEEE Computer Society

United States

Publication History

Published: 09 July 2009

Author Tags

  1. AntiVirus detection engine analyis
  2. cluster analysis
  3. malware detection

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Cited By

View all
  • (2014)Antivirus securitySoftware—Practice & Experience10.1002/spe.219744:10(1201-1222)Online publication date: 1-Oct-2014
  • (2013)Using agent technologies to correlate and compare anti-malware softwareProceedings of the 2nd annual conference on Research in information technology10.1145/2512209.2512212(17-22)Online publication date: 1-Oct-2013
  • (2013)A clinical study of risk factors related to malware infectionsProceedings of the 2013 ACM SIGSAC conference on Computer & communications security10.1145/2508859.2516747(97-108)Online publication date: 4-Nov-2013
  • (2013)Does Malware Detection Improve with Diverse AntiVirus Products? An Empirical StudyProceedings of the 32nd International Conference on Computer Safety, Reliability, and Security - Volume 815310.1007/978-3-642-40793-2_9(94-105)Online publication date: 24-Sep-2013

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