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An Empirical Study of Malware Evolution Archit Gupta, Pavan Kuppili, Aditya Akella and Paul Barford
 

Summary: An Empirical Study of Malware Evolution
Archit Gupta, Pavan Kuppili, Aditya Akella and Paul Barford
University of Wisconsin-Madison
Abstract--The diversity, sophistication and availability of mali-
cious 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 "likely"
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.
I. INTRODUCTION

  

Source: Akella, Aditya - Department of Computer Sciences, University of Wisconsin at Madison
Barford, Paul - Department of Computer Sciences, University of Wisconsin at Madison

 

Collections: Computer Technologies and Information Sciences