Open Access
MATEC Web Conf.
Volume 309, 2020
2019 International Conference on Computer Science Communication and Network Security (CSCNS2019)
Article Number 02012
Number of page(s) 7
Section Network Security and Software Design
Published online 04 March 2020
  1. YANG l, YU Q. Dynamically-enabled Cyber Defense[M]. Beijing: The People’s Posts and Telecommunications Publishing House, 2018:34–35 [Google Scholar]
  2. Baker S. Trustworthy Cyberspace: Strategic Plan for the Federal Cybersecurity Research and Development Program[R]. [Google Scholar]
  3. ategic_plan_2011 .pdf, 2011. [Google Scholar]
  4. S. Roy, C. Ellis, S. Shiva, D. Dasgupta, V. Shandilya, and Q. W. Q. Wu. A survey of game theory as applied to network security[C]. in Proc. 2017 43rd Hawaii Int. Conf. Syst. Sci., 2017, pp. 1–10. [Google Scholar]
  5. Y. Liu, C. Comaniciu, and H. Man. A bayesian game approach for intrusion detection in wireless ad hoc networks. ACM International Conference Proceeding Series. 2006, 99 [Google Scholar]
  6. H. Otrok, N.Mohammed, L. Wang, M.Debbabi, P. Bhattacharya. A game-theoretic intrusion detection model for mobile ad hoc networks Computer Communications, 2008, 31(4),708~721 [Google Scholar]
  7. Assane Gueye, Jean C. Walrand. Security in Networks: A Game-Theoretic Approach. Proceedings of the 47th IEEE Conference on Decision and Control Cancun, Mexico. 2008, 829~834 [Google Scholar]
  8. Karin Sallhammar, Bjarne E. Helvik, Svein J. Knapskog. On stochastic modeling for integrated security and dependability evaluation. Journal of Networks, 2006, 1(5) [Google Scholar]
  9. SHI J, LU Y, XIE L. Dynamic Intrusion Response Based on Game Theory. Journal of Computer Research and Development. 2008, 45 (5): 747~757. [Google Scholar]
  10. LIN W Q, WANG H, LIU J H. Research on active defense technology in network security based on non-cooperative dynamic game theory [J]. Journal of Computer Research and Development, 2013, 48(2): 306–316. [Google Scholar]
  11. BURKE D. Towards a game theory model of information warfare [D]. Montgomery: Air University, 2013. [Google Scholar]
  12. LIU Y L, FENG D G, WU L H. Performance evaluation of worm attack and defense strategies based on static Bayesian game [J]. Journal of Software, 2013, 23(3): 712–723. [Google Scholar]
  13. GAO X, ZHU Y F. DDoS defense menchanism analysis based on signaling game model[C]//The 5th International Conference on the Computer Security Institute. San Francisco, c2013: 414–417. [Google Scholar]
  14. LIN J Q, LIU P, JING J W. Using signaling games to model the multi-step attack-defense scenarios on confidentiality[J]. Security Lecture Notes in Computer Science, 2014, 39(6): 118–137. [Google Scholar]
  15. ZHANG H W, YU D K, HAN J H et al. Defense policies selection method based on attack-defense signaling game model [J]. Journal on Communications, 2016(5):51–61. [Google Scholar]
  16. JIANG L, ZHANG H W, WANG J D. Optimal strategy selection method for moving target defense based on signaling game[J]. Journal on Communications, 2019(6). [Google Scholar]
  17. ZHANG H W, YANG H P. Defense Decision-Marking Method for Anti-apt Attack Based on Attack-Defense Signaling Game[J]. Computer Engineering and Design, 2019, 40(01):67–72. [Google Scholar]
  18. Chowdhary A, Sengupta S, Huang D, et al. Markov Game Modeling of Moving Target Defense for Strategic Detection of Threats in Cloud Networks[J]. 2018. [Google Scholar]
  19. Zhou Y, Guang C. A cost-effective shuffling method against DDoS attacks using Moving Target Defense[J]. 2019. [Google Scholar]
  20. H. Maleki, S.Valizadeh, W.Koch, A. Bestavros, and M. van Dijk, ‘ ‘Markov modeling of moving target defense games,” Proc. ACMWorkshop Moving Target Defense (MTD), Oct. 2016, pp. 81_92 [Google Scholar]
  21. Z. Yong, T. Xiaobin, C. Xiaolin, et al., Network security situation awareness approach based on Markov game model, J. Softw. 22 (3) (2011) 495–508. [CrossRef] [Google Scholar]
  22. C. Lei, D.H. Ma, H.Q. Zhang, Optimal strategy selection for moving target defense based on Markov game, IEEE Access 1 (2017) 367–382. [Google Scholar]
  23. Lei C, Zhang H Q, Wang L M, et al. Incomplete Information Markov Game Theoretic Approach to Strategy Generation for Moving Target Defense[J]. Computer Communications, 2018, 116:184–199. [CrossRef] [Google Scholar]
  24. HUANG S R, ZHANG H W, WANG J D, et al. Network security threat warning method based on qualitative differential game[J]. Journal on Communications, 2018(8):29–36. [Google Scholar]
  25. ZHANG H W, LI T, HUANG S R. Network Defense Decision-Making Method Based on Attack-Defense Differential Game[J]. Acta Electronica Sinica, 2018, v.46;No.424(06):151–158. [Google Scholar]
  26. ZHANG H W, HUANG S R. Markov Differential Game Model and Its Application in Network Security[J]. Acta Electronica Sinica, 2019, 47(3):606–612. [Google Scholar]
  27. Guo R, Chang G, Qin Y, et al. Research on active defense strategy of counter DDoS attacks based on Differential Games Model[C]//International Workshop on Knowledge Discovery & Data Mining. 2008. [Google Scholar]
  28. Yang L X, Li P, Zhang Y, et al. Effective Repair Strategy Against Advanced Persistent Threat: A Differential Game Approach[J]. IEEE Transactions on Information Forensics and Security, 2019, 14(7):1713–1728. [CrossRef] [Google Scholar]
  29. LI P D, YANG, X F. On Dynamic Recovery of Cloud Storage System Under Advanced Persistent Threats. IEEE Access. PP. 1–1. 10.1109/ACCESS.2019.2932020. [Google Scholar]
  30. SUN W. Research on Attack and Deference in Information Security Based on Evolutionary Game [J]. Information Science, 2015, 23(9): 1408–1412. [Google Scholar]
  31. ZHU J M. Evaluation Model of Information Security Technologies Based on Game Theoretic [J]. Chinese Journal of Computers, 2015, 5(4): 828–834. [Google Scholar]
  32. ZHU J M, SONG B, HUANG Q F. Evolution game model of offense-defense for network security based on system dynamics [J]. Journal on Communications, 2014, 35(1): 54–61. [Google Scholar]
  33. D. Cheng, F. He, H. Qi, and T. Xu, Modeling, nalysis and control of networked evolutionary games, IEEE Transactions on Automatic Control. 2015, 99(3): 41–49. [Google Scholar]
  34. Steven Tadelis. Game Theory: An Introduction[M]. Princeton: Princeton University Press, 2014. [Google Scholar]
  35. WANG Y Z, YU J Y, QIU W. Evolutionary Game Model and Analysis Methods for Network Group Behavior [J]. Chinese Journal of Computers. 2015, 38(2): 282–300. [Google Scholar]
  36. Shigen Shen, Changyuan Jiang, Hua Jiang, et al. Evolutionary Game Based Dynamics of Trust Decision in WSNs[C]. 2016 International Conference on Sensor Network Security Technology and Privacy Communication System (SNS & PCS), 2016, 49–56. [Google Scholar]
  37. Lye K W, Jeannette W. Markov Game strategies in network security [J]. International Journal of Information Security, 2008, 4(1): 71–86. [Google Scholar]
  38. HUANG J M, ZHANG H W, WANG H J, et al. A Method for Selecting Defense Strategies Based on Stochastic Evolutionary Game Model[J]. Acta Electronica Sinica. [Google Scholar]
  39. HUANG J M, ZHANG H W. Improving replicator dynamic evolutionary game model for selecting optimal defense strategies[J]. Journal on Communications,2018. [Google Scholar]
  40. Alabdel Abass A A, Xiao L, Mandayam N B, et al. Evolutionary Game Theoretic Analysis of Advanced Persistent Threats Against Cloud Storage[J]. IEEE Access, 2017, 5:8482–8491. [CrossRef] [Google Scholar]
  41. Qiu Y, Chen Z, Xu L. Active Defense Model of Wireless Sensor Networks Based on Evolutionary Game Theory[C]//International Conference on Wireless Communications Networking & Mobile Computing. IEEE, 2010. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.