A game theoretic model for dynamic configuration of large-scale intrusion detection signatures

被引:0
|
作者
Xaiver Jerald Punithan
Jong-Deok Kim
Dongseok Kim
Yoon-Ho Choi
机构
[1] SNU,School of Electrical and Computer Engineering
[2] School of Computer Science and Engineering,undefined
[3] PNU,undefined
[4] Department of Mathematics,undefined
[5] KGU,undefined
来源
关键词
Game; Network security; Intrusion detection signature; Dynamic configuration;
D O I
暂无
中图分类号
学科分类号
摘要
In this paper, we note that the signature-based intrusion detection system (S-IDS) can cause the low accuracy against mutants of intrusion packets. This is because the S-IDS commonly detects network intrusion in data flows by identifying the existence of the predefined intrusion signatures, which is called static intrusion signature configuration (SISC). To increase the accuracy, all intrusion signatures corresponding to all possible mutants of a pertinent attack may be activated. However, the static intrusion signature configuration with all possible intrusion signatures can largely increase the size of storage and the signature search time in the process of signature analysis. To solve the problems that occur when activating all possible intrusion signatures, we propose a two-player non-cooperative zero-sum game with incomplete information for dynamic intrusion signature configuration (DISC), where the various lengths of an intrusion signature have been activated in a time-shared manner. After formulating the problem into the game theoretic approach, we found the optimal strategy for DISC in the S-IDS. To the best of our knowledge, this work is the first approach that analyzes the optimal DISC strategy against the various mutants of intrusion packets. From evaluation results, we show that the DISC by the defender is more effective than the SISC against various mutants of intrusion packets by the intruder.
引用
收藏
页码:15461 / 15477
页数:16
相关论文
共 50 条
  • [31] Intrusion Detection with Segmented Federated Learning for Large-Scale Multiple LANs
    Sun, Yuwei
    Ochiai, Hideya
    Esaki, Hiroshi
    2020 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2020,
  • [32] Large-scale network intrusion detection based on distributed learning algorithm
    Daxin Tian
    Yanheng Liu
    Yang Xiang
    International Journal of Information Security, 2009, 8 : 25 - 35
  • [33] PRISM: A Hierarchical Intrusion Detection Architecture for Large-Scale Cyber Networks
    Javed Y.
    Khayat M.A.
    Elghariani A.A.
    Ghafoor A.
    IEEE Transactions on Dependable and Secure Computing, 2023, 20 (06) : 5070 - 5086
  • [34] A Game-Theoretic Perspective on Resource Management for Large-Scale UAV Communication Networks
    Chen, Jiaxin
    Chen, Ping
    Wu, Qihui
    Xu, Yuhua
    Qi, Nan
    Fang, Tao
    CHINA COMMUNICATIONS, 2021, 18 (01) : 70 - 87
  • [35] Baryonic signatures in large-scale structure
    Meiksin, A
    White, M
    Peacock, JA
    MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 1999, 304 (04) : 851 - 864
  • [36] Baryonic signatures in large-scale structure
    Institute for Astromomy, University of Edinburgh, Royal Observatory, Blackford Hill, Edinburgh EH9 3HJ, United Kingdom
    不详
    Mon. Not. R. Astron. Soc., 4 (851-864):
  • [37] An Intrusion Detection Game Theoretical Model
    Otrok, Hadi
    Zhu, Benwen
    Yahyaoui, Hamdi
    Bhattacharya, Prabir
    INFORMATION SECURITY JOURNAL, 2009, 18 (05): : 199 - 212
  • [38] Balancing Large-Scale Wildlife Protection and Forest Management Goals with a Game-Theoretic Approach
    Yemshanov, Denys
    Haight, Robert G.
    Liu, Ning
    Rempel, Robert S.
    Koch, Frank H.
    Rodgers, Art
    FORESTS, 2021, 12 (06):
  • [39] Expanding Access to Large-Scale Genomic Data While Promoting Privacy: A Game Theoretic Approach
    Wan, Zhiyu
    Vorobeychik, Yevgeniy
    Xia, Weiyi
    Clayton, Ellen Wright
    Kantarcioglu, Murat
    Malin, Bradley
    AMERICAN JOURNAL OF HUMAN GENETICS, 2017, 100 (02) : 316 - 322
  • [40] A Novel Decentralized Game-Theoretic Adaptive Traffic Signal Controller: Large-Scale Testing
    Abdelghaffar, Hossam M.
    Rakha, Hesham A.
    SENSORS, 2019, 19 (10):