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Automated Construction of Malware Families

  • Krishnendu GhoshEmail author
  • Jeffery Mills
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11611)

Abstract

Discovery of malware families from behavioral characteristics of a set of malware traces is an important step in the detection of malware. Malware in the wild often occur as variants of each other. In this work, a data dependent formalism is described for the construction of malware families from trace data. The malware families are represented in an edge labeled graph where the nodes represent a malware trace and edges describe relationship between the malware traces. The edge labels contain a numerical value representing similarity between the malware traces. Network theoretical concepts such as hubs are evaluated on the edge labeled graph. The formalism has been elucidated by the experiments performed on multiple data sets of malware traces.

Keywords

Malware Families Malware Traces Kullback-Leibler divergence Discrete-Time Markov Chain Algorithm Network theory 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer ScienceCollege of CharlestonCharlestonUSA
  2. 2.Department of Computer ScienceNorthern Kentucky UniversityHighland HeightsUSA

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