Scheduling Algorithm Based on Heterogeneity and Confidence for Mimic Defense
As a defense technology with endogenous security, mimic defense plays an important role in network security research. The scheduling of executors is one of the severe problems to take into account for mimic defense, and current research lacks comprehensive consideration of the influence of system architecture and attack behavior on scheduling algorithm. Based on previous research, this paper first introduces concept of heterogeneity and confidence according to vulnerability attributes and attack distribution characteristics to characterize the executors. Moreover, the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) algorithm is brought in to optimize the system security and improve operating efficiency. Experimental results showed that,compared with the existing algorithms, Random, MD, RSMS, it improves the security of the system in non-uniform distributed attack scenario and the operating efficiency in each attack scenario.
E.Cole, Network security bible, John Wiley & Sons, 2011.
J. H. Cho,et al., Toward Proactive, Adaptive Defense: A Survey on Moving Target Defense,Ieee Communications Surveys and Tutorials, 22(1): 709-745, 2020.
J. X. Wu, Intention and vision of mimic computing and mimic security defense, Telecommunications Science, 30 (7): 2-7, 2014.
J. J. Zheng, and A. S.Namin, A Survey on the Moving Target Defense Strategies: An Architectural Perspective, Journal of Computer Science and Technology, 34(1): 207-233, 2019.
J. X. Wu, Research on mimic defense in cyberspace. Journal of information security, (4): 1-10, 2016.
C. Qi, et al., An aware-scheduling security architecture with priority-equal multi-controller for SDN, China Communications, 14(9): 144-154, 2017.
H. C. Hu, et al., MNOS: a mimic network operating system for software defined networks, IET Information Security, 11(6): 345-355, 2017.
Z. Zhang, B. L. Ma, andJ. X.Wu, Test and analysis of web server mimic defense principle verification system, Journal of information security, 2 (01): 13-28, 2017.
L. M. Pu, et al., Heterogeneous executor scheduling algorithm for mimic cloud service, Journal on Communications, 41 (03): 17-24, 2020.
K. Song,et al., Endogenous security architecture of Ethernet switch based on mimic defense, Journal on Communications, 41 (5): 18-26, 2020.
W. J. Zhang,et al., A programmable semantic parsing method for mimic judgment, Journal on Communications, 41 (4): 62-69, 2020.
H. C. Hu,et al., Mimic defense: a designed-in cybersecurity defense framework, IET Information Security, 12(3): 226-237, 2017.
W.Guo,et al., Scheduling Sequence Control Method Based on Sliding Window in Cyberspace Mimic Defense, IEEE Access, 8: 1517 - 1533, 2019.
C. Qi,et al. Dynamic-scheduling mechanism of controllers based on security policy in software-defined network, Electronics letters, 52(23): 1918-1920, 2016.
C. H. Li, et al., Mimic defense method of service deployment in SDN. Journal on Communications, 39 (S2): 121-130, 2018.
Q. R. Liu, S. J. Lin, and Z. Y.Gu, Heterogeneous functional equivalence scheduling algorithm for mimic security defense, Journal on Communications, 39 (07): 188-198, 2018.
J. X. Zhang, J. M. Pang, Z. Zhang. A mimic structured method to quantify the heterogeneity of web servers, Journal on Communications, 31 (02): 564-577, 2020.
Z. Q. Wu, et al., A mimic ruling optimization method based on executive heterogeneity, Computer Engineering: 1-8, 2019.
M.Behzadian,et al., A state-of the-art survey of TOPSIS applications, Expert Systems with applications, 39(17): 13051-13069, 2012.
M. Garcia,et al., OS diversity for intrusion tolerance: Myth or reality?, IEEE/IFIP 41st International Conference on Dependable Systems & Networks (DSN), Hong Kong: 383-394, 2011.
M. Garcia,et al., Analysis of operating system diversity for intrusion tolerance, Software-Practice & Experience, 44(6): 735-770, 2014.