Preventive portfolio against data-selling ransomware-A game theory of encryption and deception

被引:7
|
作者
Li, Zhen [1 ]
Liao, Qi [2 ]
机构
[1] Albion Coll, Dept Econ & Management, Albion, MI 49224 USA
[2] Cent Michigan Univ, Dept Comp Sci, Mt Pleasant, MI 48859 USA
关键词
Computer and network security; Cybersecurity; Data-selling ransomware; Preventive portfolio; Encryption; Deception; Game theory; Economics; TAXONOMY;
D O I
10.1016/j.cose.2022.102644
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Ransomware has risen to be among the top cyber threats in recent years. There is an alarming trend of ransomware stealing data in addition to locking files. Compared to traditional ransomware, this new data selling ransomware can be more harmful to the victims facing the data leakage threat. Traditional wisdom of defensive measures such as data backup is less effective in preventing the attacker from making money by selling data. We propose two preventive measures designed to defend against the data-selling ransomware, i.e., preventive data encryption and preventive data deception. Users may form a preventive portfolio made up of the two preventive measures. We contribute a novel game theoretical model of the data-selling ransomware to study the equilibrium strategies of the attacker and victims. The equilibrium solution of the portfolio and tradeoff analysis of both data encryption and deception are particularly useful for the users to optimize their system to defend against ransomware attacks. Simulation studies demonstrate the effectiveness of the preventive portfolio, which maximizes user utility while significantly reducing the profit of the attacker.(c) 2022 Elsevier Ltd. All rights reserved.
引用
收藏
页数:11
相关论文
共 3 条
  • [1] Game Theory of Data-selling Ransomware
    Li Z.
    Liao Q.
    Journal of Cyber Security and Mobility, 2021, 10 (01): : 65 - 96
  • [2] Security, QoS and energy aware optimization of cloud-edge data centers using game theory and homomorphic encryption: Modeling and formal verification
    Marwan, Mbarek
    Temghart, Abdelkarim Ait
    Ouhmi, Said
    Lazaar, Mohamed
    RESULTS IN ENGINEERING, 2024, 24
  • [3] Game Theory based Optimal Defensive Resources Allocation with Incomplete Information in Cyber-physical Power Systems against False Data Injection Attacks
    Yan, Bingjing
    Jiang, Zhenze
    Yao, Pengchao
    Yang, Qiang
    Li, Wei
    Zomaya, Albert Y.
    PROTECTION AND CONTROL OF MODERN POWER SYSTEMS, 2024, 9 (02) : 115 - 127