Evolutionary Game Theoretic Analysis of Advanced Persistent Threats Against Cloud Storage

被引:33
|
作者
Abass, Ahmed A. Alabdel [1 ,2 ]
Xiao, Liang [3 ]
Mandayam, Narayan B. [2 ]
Gajic, Zoran [2 ]
机构
[1] Univ Thiqar, Dept Elect Engn, Nasiriyah, Iraq
[2] Rutgers State Univ, Dept Elect & Comp Engn, Wireless Informat Network Lab, New Brunswick, NJ 08816 USA
[3] Xiamen Univ, Dept Commun Engn, Xiamen, Peoples R China
来源
IEEE ACCESS | 2017年 / 5卷
基金
美国国家科学基金会; 中国国家自然科学基金;
关键词
Evolutionary game theory; advanced persistent threats; cloud storage; replicator dynamics;
D O I
10.1109/ACCESS.2017.2691326
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:8482 / 8491
页数:10
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