Computer Science ›› 2022, Vol. 49 ›› Issue (11A): 211200296-6.doi: 10.11896/jsjkx.211200296

• Information Security • Previous Articles     Next Articles

Mimic Firewall Executor Scheduling Algorithm Based on Executor Defense Ability

LIU Wen-he, JIA Hong-yong, PAN Yun-fei   

  1. School of Cyber Science and Engineering,Zhengzhou University,Zhengzhou 450000,China
  • Online:2022-11-10 Published:2022-11-21
  • About author:LIU Wen-he,born in 1999,postgra-duate.His main research interests include cyber security and mimic defense.
  • Supported by:
    Science and Technology Research Plan of Henan Province(192102210115) and Collaborative Innovation Major Project of Zhengzhou City(20XTZX-X010).

Abstract: Mimic defense technology is an effective means to solve the easy to attack but difficult to defend situation in existing network environment.Mimic defense technology builds a safe and reliable system by improving the dynamics,heterogeneity and randomness of the system.The scheduling of heterogeneous executive bodies is the key link of mimic defense.Existing scheduling algorithms lack of situational awareness and can only schedule the executor according to the existing strategy,which has the problem of poor applicability.For this reason,DCOE,a scheduling algorithm based on the comprehensive defense capability of the executive body is proposed.Based on the classic traffic monitoring algorithm,DCOE identifies the threat type and threat level of the current traffic,and dynamically adjusts the types and numbers of heterogeneous executives according to the defense capabilities of each executive against the current traffic.Simulation experiments show that,the DCOE algorithm can reduce the failure rate and escape rate of the system on the basis of reducing the number of scheduling heterogeneous executives,that is,improve the overall defense level of the system on the premise of reducing the system overhead,and increase the difficulty of the adversary’s attack.

Key words: Mimic defense, Heterogeneous executor, Scheduling algorithm, Executor defense ability, Simulation

CLC Number: 

  • TP393.08
[1]National Science and Technology Council.“Trustworthy cyberspace:Strategic plan for the federal cybersecurity research and development program”[OL].https://www.nitrd.gov/SUBCOMMITTEE/csia/ed_Cybersecurity_RD_Strategic_Plan_2011.pdf.
[2]SHI L Y,JIA C F,LYU S W.Research onendhopping for active network confrontation [J].Journal on Communications,2008(2):106-110.
[3]WU J X.Research on Cyber Mimic Defense[J].Journal of Cyber Security,2016,1(4):1-10.
[4]WU JX,LI J F,ZHANG F,et al.A heterogeneous redundancies scheduling equipment and method[P].China,CN106161417A,2016-11-23.
[5]LIU Q R,LIN S J,GU Z Y.Heterogeneous redundancies scheduling algorithm for mimic security defense[J].Journal on Communications,2018,39(7):188-198.
[6]PU LM,LIU S X,DING R H,et al.Heterogeneous executor scheduling algorithm for mimic cloud service[J].Journal on Communications,2020,41(3):17-24.
[7]GAO Y,ZI C C,FENG S F,et al.Security Scheduling Algorithm for Web Gateways Based on Mimicry Defense Theory[J].Journal of Chinese Computer Systems,2021,42(9):1913-1919.
[8]ZHU Z B,LIU Q R,LIU D P,et al.Research progress of mimic multi-execution scheduling algorithm[J].Journal on Communications,2021,42(5):179-190.
[9]WEI S,YU H,GU Z Y,et al.Architecture of mimic securityprocessor for industry control syste[J].Journal of Cyber Security,2017,2(1):54-73.
[10]LECUN Y,BOTTOU L,BENGIO Y,et al.Gradient basedlearning applied to document recognition[J].Proceedings of the IEEE,1998,86(11):2278-2324.
[11]FIRST.Common vulnerability scoring system(Version-3.1)[EB/OL].(2019-01-01)[2021-03-16].https://www.first.org/cvss/calculator/3.1.
[12]GHARIB A,SHARAFALDIN I,LASHKARI A H,et al.AnEvaluation Framework for Intrusion Detection Dataset [C]//2016 International Conference on Information Science and Security(ICISS).IEEE,2017.
[13]LIU M J,WANG X F,HUANG Y L.Preprocessing in data mi-ning[J].Computer Science,2000,27(4):56-59.
[14]HU H C,CHEN F C,WANG Z P.Performance evaluationsonDHR for cyberspace mimic defense[J].Journal of Cyber Security,2016,1(4):40-51.
[15]WU J X.Robust control and endogenous safety[J].CivIntegration on Cyberspace,2018(3):23-27.
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