By Topic

An empirical study of malware evolution

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Gupta, A. ; Univ. of Wisconsin-Madison, Madison, WI ; Kuppili, P. ; Akella, A. ; Barford, P.

The diversity, sophistication and availability of malicious software (malcode/malware) pose enormous challenges for securing networks and end hosts from attacks. In this paper, we analyze a large corpus of malcode meta data compiled over a period of 19 years. Our aim is to understand how malcode has evolved over the years, and in particular, how different instances of malcode relate to one another. We develop a novel graph pruning technique to establish the inheritance relationships between different instances of malcode based on temporal information and key common phrases identified in the malcode descriptions. Our algorithm enables a range of possible inheritance structures. We study the resulting ldquolikelyrdquo malcode families, which we identify through extensive manual investigation. We present an evaluation of gross characteristics of malcode evolution and also drill down on the details of the most interesting and potentially dangerous malcode families.

Published in:

Communication Systems and Networks and Workshops, 2009. COMSNETS 2009. First International

Date of Conference:

5-10 Jan. 2009