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Systematic Classification of Attackers via Bounded Model Checking

  • Eric Rothstein-MorrisEmail author
  • Jun Sun
  • Sudipta Chattopadhyay
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11990)

Abstract

In this work, we study the problem of verification of systems in the presence of attackers using bounded model checking. Given a system and a set of security requirements, we present a methodology to generate and classify attackers, mapping them to the set of requirements that they can break. A naive approach suffers from the same shortcomings of any large model checking problem, i.e., memory shortage and exponential time. To cope with these shortcomings, we describe two sound heuristics based on cone-of-influence reduction and on learning, which we demonstrate empirically by applying our methodology to a set of hardware benchmark systems.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Eric Rothstein-Morris
    • 1
    Email author
  • Jun Sun
    • 2
  • Sudipta Chattopadhyay
    • 1
  1. 1.Singapore University of Technology and DesignSingaporeSingapore
  2. 2.Singapore Management UniversitySingaporeSingapore

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