
CLC number: TP393
On-line Access: 2025-06-04
Received: 2024-04-02
Revision Accepted: 2024-10-22
Crosschecked: 2025-09-04
Cited: 0
Clicked: 480
Citations: Bibtex RefMan EndNote GB/T7714
Sisi SHAO, Zhibo HE, Shangdong LIU, Weili ZHANG, Fei WU, Fukang ZENG, Jun ZUO, Longfei ZHOU, Yukun NIU, Yimu JI. Output difference feedback and system benefit control based dynamic heterogeneous redundancy architecture[J]. Frontiers of Information Technology & Electronic Engineering,in press.https://doi.org/10.1631/FITEE.2400251 @article{title="Output difference feedback and system benefit control based dynamic heterogeneous redundancy architecture", %0 Journal Article TY - JOUR
基于输出差异反馈和系统效益控制的动态异构冗余架构左军3,7,周龙飞3,7,牛玉坤5,季一木3,5,7,8 1南京邮电大学物联网学院,中国南京市,210023 2西交利物浦大学国际商学院,中国苏州市,215123 3南京邮电大学计算机学院,中国南京市,210023 4信息工程大学外国语学院,中国郑州市,450006 5紫金山实验室,中国南京市,211111 6南京邮电大学自动化学院,中国南京市,210023 7南京邮电大学高性能计算与大数据研究所,中国南京市,210003 8中国高性能计算南京分中心,中国南京市,210003 摘要:拟态主动防御技术通过引入动态异构冗余架构来有效扰乱攻击路线,降低攻击成功率。然而,现有方法忽略裁决机制在复杂可变网络环境中的适应性,往往聚焦系统安全性而忽视系统性能。为解决前述局限,本文提出一种基于输出差异反馈和系统效益控制的动态异构冗余架构。该架构引入一种基于输出差异反馈的裁决机制,通过量化各执行体输出偏差对全局裁决结果的影响来增强适应性。此外,该架构结合一种基于系统效益的调度策略,将服务质量和切换开销建模为双目标优化问题,在降低计算成本和系统开销的同时平衡系统安全。仿真结果表明,该架构增强了对不同网络环境的适应能力,有效降低了攻击成功率和平均裁决失败率。 关键词组: Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article
Reference[1]Cho JH, Sharma DP, Alavizadeh H, et al., 2020. Toward proactive, adaptive defense: a survey on moving target defense. IEEE Commun Surv Tut, 22(1):709-745. ![]() [2]Fu T, Zhen W, Yang F, et al., 2022. Mimic defense equivalent scheduling algorithm based on service quality and credit. IEEE 6th Information Technology and Mechatronics Engineering Conf, p.414-419. ![]() [3]Hu HC, Wu JX, Wang ZP, et al., 2018. Mimic defense: a designed-in cybersecurity defense framework. IET Inform Secur, 12(3):226-237. ![]() [4]Hu JJ, Li Y, Li ZZ, et al., 2024. Unveiling the strategic defense mechanisms in dynamic heterogeneous redundancy architecture. IEEE Trans Netw Serv Manag, 21(4):4912-4926. ![]() [5]Jiang DD, Wang ZH, Huo LW, et al., 2021. A performance measurement and analysis method for software-defined networking of IoV. IEEE Trans Intell Transp Syst, 22(6):3707-3719. ![]() [6]Jiang DD, Wang F, Lv ZH, et al., 2023. QoE-aware efficient content distribution scheme for satellite-terrestrial networks. IEEE Trans Mob Comput, 22(1):443-458. ![]() [7]Jiang DD, Wang ZH, Wang Y, et al., 2024. A blockchain-reinforced federated intrusion detection architecture for IIoT. IEEE Int Things J, 11(16):26793-26805. ![]() [8]Li GS, Wang W, Gai KK, et al., 2021. A framework for mimic defense system in cyberspace. J Signal Process Syst, 93(2):169-185. ![]() [9]Lin SJ, Liu QR, Wang XL, 2018. Competitive arbitration model for mimic defense system. Comput Eng, 44(4):193-198 (in Chinese). ![]() [10]Lin X, Wu J, Li JH, et al., 2023. Heterogeneous differential-private federated learning: trading privacy for utility truthfully. IEEE Trans Depend Secur Comput, 20(6):5113-5129. ![]() [11]Liu QR, Lin SJ, Gu ZY, 2018. Heterogeneous redundancies scheduling algorithm for mimic security defense. J Commun, 39(7):188-198 (in Chinese). ![]() [12]Lu YQ, Huang JX, Cheng Z, et al., 2021. A multi-index mimic voting algorithm based on improved AHP-FCE model. J Beijing Univ Posts Telecommun, 44(2):8-13 (in Chinese). ![]() [13]Lu ZP, Chen FC, Cheng GZ, et al., 2017. Towards a dynamic controller scheduling-timing problem in software-defined networking. China Commun, 14(10):26-38. ![]() [14]Lucy W, 2024. Algorithms and adjudication. Jurisprudence, 15(3):251-281. ![]() [15]Rehman Z, Gondal I, Ge MM, et al., 2024. Proactive defense mechanism: enhancing IoT security through diversity-based moving target defense and cyber deception. Comput Secur, 139:103685. ![]() [16]Ren Q, Wu JX, He L, 2020. Performance modeling based on GSPN for cyberspace mimic DNS. Chin J Electron, 29(4):738-749. ![]() [17]Shao SS, Ji YM, Zhang WL, et al., 2023a. A DHR executor selection algorithm based on historical credibility and dissimilarity clustering. Sci China Inform Sci, 66(11):212304. ![]() [18]Shao SS, Liu SD, Li K, et al., 2023b. LBA-EC: load balancing algorithm based on weighted bipartite graph for edge computing. Chin J Electron, 32(2):313-324. ![]() [19]Tong Q, Guo YF, 2021. A comprehensive evaluation of diversity systems based on mimic defense. Sci China Inform Sci, 64(12):229304. ![]() [20]Wang YW, Wu JX, Guo YF, et al., 2018. Scientific workflow execution system based on mimic defense in the cloud environment. Front Inform Technol Electron Eng, 19(12):1522-1536. ![]() [21]Wang ZH, Jiang DD, Wang F, et al., 2021. A polymorphic heterogeneous security architecture for edge-enabled smart grids. Sustain Cities Soc, 67:102661. ![]() [22]Wang ZH, Jiang DD, Lv ZH, 2023. AI-assisted trustworthy architecture for industrial IoT based on dynamic heterogeneous redundancy. IEEE Trans Ind Inform, 19(2):2019-2027. ![]() [23]Wei D, Xiao L, Shi L, et al., 2022. Mimic web application security technology based on DHR architecture. Proc Int Conf on Artificial Intelligence and Intelligent Information Processing, p.118-124. ![]() [24]Wu JX, 2022a. Cyberspace endogenous safety and security. Engineering, 15:179-185. ![]() [25]Wu JX, 2022b. Development paradigms of cyberspace endogenous safety and security. Sci China Inform Sci, 65(5):156301. ![]() [26]Wu T, Hu CN, Chen QN, et al., 2021. Defense-enhanced dynamic heterogeneous redundancy architecture based on executor partition. J Commun, 42(3):122-134 (in Chinese). ![]() [27]Yadav D, Raj BAA, 2024. An efficient swarm intelligence algorithm for multi-objective task scheduling optimization in the context of cloud computing. Int Conf on Automation and Computation, p.148-152. ![]() [28]Yu F, Liu K, Geng YY, et al., 2022. Multi executor decision algorithm and scheduling algorithm based on differential distance feedback. Appl Res Comput, 39(5):1437-1443 (in Chinese). ![]() [29]Zhang JX, Pang JM, Zhang Z, 2020. Quantification method for heterogeneity on web server with mimic construction. J Softw, 31(2):564-577 (in Chinese). ![]() [30]Zheng Y, Li Z, Xu XL, et al., 2022. Dynamic defenses in cyber security: techniques, methods and challenges. Digit Commun Netw, 8(4):422-435. ![]() [31]Zhu ZB, Liu QR, Liu DP, et al., 2021. Research progress of mimic multi-execution scheduling algorithm. J Commun, 42(5):179-190 (in Chinese). ![]() Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou
310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn Copyright © 2000 - 2025 Journal of Zhejiang University-SCIENCE | ||||||||||||||


ORCID:
Open peer comments: Debate/Discuss/Question/Opinion
<1>