Life Cycle Pattern Study of Malicious Codes

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Author(s): June C. Wei (University of West Florida, USA), Randall Reid (University of West Florida, USA) and Hongmei Zhang (University of South Carolina, USA)
Copyright: 2011
Pages: 16
Source title: Pervasive Information Security and Privacy Developments: Trends and Advancements
Source Author(s)/Editor(s): Hamid Nemati (The University of North Carolina at Greensboro, USA)
DOI: 10.4018/978-1-61692-000-5.ch014

Keywords: Information Science Reference / Information Security & Privacy / IT Security and Ethics / Security & Forensics

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Abstract

This chapter investigates the patterns of malicious code attacks based on monthly data of the top 10 virus shares from 1998 to 2005. Three parameters were identified for study, overall pattern of the attack, the number reentries into the top 10 most prevalent attacks, and the maximum percentage share. The dataset was validated by comparing it to an independent dataset that measured the same parameters for a subset of the period of the primary dataset. The effects of malicious code that started before or disappeared outside the collection period were found to not have a significant effect. A multivariate regression analysis showed that the number of entries and the maximum share had a strong relationship with the visible life span. Multivariate cluster analysis was conducted on the reentry parameters and yielded six virus clusters classifications. The high impact viruses, 43 of the 230, are identified and further grouped.

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Life Cycle Pattern Study of Malicious Codes

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