4.6 Article

Evolutionary Game Theoretic Analysis of Advanced Persistent Threats Against Cloud Storage

期刊

IEEE ACCESS
卷 5, 期 -, 页码 8482-8491

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2017.2691326

关键词

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

资金

  1. National Science Foundation [ACI-1541069]
  2. Higher Committee for Education Development in Iraq
  3. National Natural Science Foundation of China [61671396]
  4. CCF-Venustech Hongyan Research Initiative [2016-010]
  5. Direct For Computer & Info Scie & Enginr
  6. Office of Advanced Cyberinfrastructure (OAC) [1541069] Funding Source: National Science Foundation

向作者/读者索取更多资源

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.

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