Evolutionary Game Theoretic Analysis of Advanced Persistent Threats Against Cloud Storage

Ahmed A.Alabdel Abass, Liang Xiao, Narayan B. Mandayam, Zoran Gajic

Research output: Contribution to journalArticlepeer-review

21 Scopus citations


Advanced Persistent Threats (APTs) represent stealthy, powerful, long-term, and well-funded attacks against cyber systems, such as data centers and cloud storage. Evolutionary game theory is used to capture the long-term continuous behavior of the APTs on the cloud storage devices. Two APT defense games with discrete strategies are formulated, in which both an APT attacker and a defender compete to control one or multiple storage devices regarding their attack or defense intervals. The dynamical stability of each defense and attack strategy pair is studied according to the replicator dynamics criteria to characterize the locally asymptotically stable equilibrium strategies. The evolutionary stable strategy is discussed in each game, which is a subset of the asymptotically stable Nash equilibrium (NE). The phase portraits provide the locally asymptotically stable points of the APT defense game, which represent the NE showing the relationship between the asymptotic stability and evolutionary stability.

Original languageEnglish (US)
Article number7892931
Pages (from-to)8482-8491
Number of pages10
JournalIEEE Access
StatePublished - 2017

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)


  • Evolutionary game theory
  • advanced persistent threats
  • cloud storage
  • replicator dynamics

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