Effectiveness Evaluation Model of Moving Target Defense Based on System Attack Surface

被引:19
|
作者
Xiong, Xin-Li [1 ]
Yang, Lin [2 ]
Zhao, Guang-Sheng [3 ]
机构
[1] Army Engn Univ PLA, Coll Command & Control Engn, Nanjing 211101, Jiangsu, Peoples R China
[2] Acad Mil Sci PLA, Syst Engn Res Inst, Beijing 100141, Peoples R China
[3] Natl Univ Def Technol, Coll Comp Sci, Changsha 410073, Hunan, Peoples R China
来源
IEEE ACCESS | 2019年 / 7卷
关键词
Information security; moving target defense; nonhomogeneous hidden Markov processes; performance evaluation;
D O I
10.1109/ACCESS.2019.2891613
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Evaluation of moving target defense (MTD) effectiveness has become one of the fundamental problems in current studies. In this paper, an evaluation model of MTD effectiveness based on system attack surface (SAS) is proposed to extend this model covering enterprise-class topology and multi-layered moving target (MT) techniques. The model is focused on the problem of incorrect performance assessment caused by inaccurately characterizing the process of attacking and defending. Existing evaluation models often fail to describe M ID dynamically in a process. To deal with this static view, offensive and defensive process based on a player's move is presented. Besides, it converts all the attack and defense actions into the process, and interactivities are evaluated by system view extended attack surface model. Previously, the proposed attack surface models are not concerned about the links between nodes and vulnerabilities affected by topologies. After comprehensively analyzing the impact of interactions in the system, a SAS model is proposed to demonstrate how resources of the system are affected by the actions of attackers and defenders, thus ensuring the correctness of parameters for SAS in measuring MT technology. Moreover, by generating a sequence of those shifting parameters, a nonhomogeneous hierarchical hidden Markov model is used to find the possible sequence of attacking states by introducing the partial Viterbi algorithm. Also, a sequence of attacking states is defined to illustrate how adversaries are handled by MT technologies and how much additional consumption costs are increased by the system resource reconfiguration. Finally, the simulation of the proposed approach is given in a case study to demonstrate the feasibility and validity of the proposed effectiveness evaluation model in a systematic and dynamic view.
引用
收藏
页码:9998 / 10014
页数:17
相关论文
共 50 条
  • [21] Mitigation of DDoS Attack Using Moving Target Defense in SDN
    Rochak Swami
    Mayank Dave
    Virender Ranga
    Wireless Personal Communications, 2023, 131 : 2429 - 2443
  • [22] Evaluating Deception and Moving Target Defense with Network Attack Simulation
    Reti, Daniel
    Elzer, Karina
    Fraunholz, Daniel
    Schneider, Daniel
    Schotten, Hans Dieter
    PROCEEDINGS OF THE 9TH ACM WORKSHOP ON MOVING TARGET DEFENSE, MTD 2022, 2022, : 45 - 53
  • [23] Reasoning about Moving Target Defense in Attack Modeling Formalisms
    Ballot, Gabriel
    Malvone, Vadim
    Leneutre, Jean
    Borde, Etienne
    PROCEEDINGS OF THE 9TH ACM WORKSHOP ON MOVING TARGET DEFENSE, MTD 2022, 2022, : 55 - 65
  • [24] Attack Graph-Based Moving Target Defense in Software-Defined Networks
    Yoon, Seunghyun
    Cho, Jin-Hee
    Kim, Dong Seong
    Moore, Terrence J.
    Free-Nelson, Frederica
    Lim, Hyuk
    IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, 2020, 17 (03): : 1653 - 1668
  • [25] Time-Based Moving Target Defense Using Bayesian Attack Graph Analysis
    Kim, Hyejin
    Hwang, Euiseok
    Kim, Dongseong
    Cho, Jin-Hee
    Moore, Terrence J.
    Nelson, Frederica F.
    Lim, Hyuk
    IEEE ACCESS, 2023, 11 : 40511 - 40524
  • [26] On Stealthiness and Effectiveness of Moving Target Defense in Smart Grids
    Wang, Jiazhou
    Tian, Jue
    Xiao, Gaoxi
    Liu, Yang
    Huang, Hao
    Zhou, Yadong
    Liu, Ting
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2025,
  • [27] Effectiveness of IP Address Randomization in Decoy-Based Moving Target Defense
    Clark, Andrew
    Sun, Kun
    Poovendran, Radha
    2013 IEEE 52ND ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), 2013, : 678 - 685
  • [28] ShuffleCAN: Enabling Moving Target Defense for Attack Mitigation on Automotive CAN
    Qian, Huiping
    Han, Hao
    Zhu, Xiaojun
    Xu, Fengyuan
    2023 19TH INTERNATIONAL CONFERENCE ON MOBILITY, SENSING AND NETWORKING, MSN 2023, 2023, : 351 - 358
  • [29] An Optimal Design of a Moving Target Defense for Attack Detection in Control Systems
    Griffioen, Paul
    Weerakkody, Sean
    Sinopoli, Bruno
    2019 AMERICAN CONTROL CONFERENCE (ACC), 2019, : 4527 - 4534
  • [30] A Signaling Game Model for Moving Target Defense
    Feng, Xiaotao
    Zheng, Zizhan
    Cansever, Derya
    Swami, Ananthram
    Mohapatra, Prasant
    IEEE INFOCOM 2017 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS, 2017,