Distributed mimic decision model and framework design

doi:10.3785/j.issn.1008-973X.2025.10.020

Journal of ZheJiang University (Engineering Science)

2025, Vol. 59

Issue (10): 2195-2204 DOI: 10.3785/j.issn.1008-973X.2025.10.020

Distributed mimic decision model and framework design

Xinsheng YU1(

),Lunhan LUO1,Fan ZHANG2,Bo ZHANG3,Danjiang ZHU1,Wei XIE1

1. The 32nd Research Institute of China Electronics Technology Group Corporation, Shanghai 201808, China
2. National Digital Switching System Engineering & Technological R&D Center, Zhengzhou 450002, China
3. China Electric Power Research Institute, Beijing 100192, China

Download:

HTML

PDF(1001KB) HTML
Export: BibTeX | EndNote (RIS)

Abstract

A mimic defense framework with a single decision unit presupposes decision algorithms based on the number of executors, which makes the number of executors unadjustable. A distributed mimic decision model was proposed, transforming the design of the output values comparing algorithm into the multi-hierarchy linked logic arithmetic topology planning. Any number of executors or fault-tolerance executor customization was supported, and the cascading topology of the logic arithmetic was adjusted dynamically. The imposed consistency between the number of executors and the decision algorithm was decoupled, and the prerequisite of the decision algorithm according to the number of executors was removed. A distributed mimic decision framework for high-security systems and high-robustness systems was designed, and the relationship between the number of executors, the tolerance and the number of iterative layers of cascading topology was quantitatively analyzed. In the simulation experiments, the capability and efficiency were compared among a mimic decision framework with a single unit, a classical triple modular redundancy voting model and the distributed mimic decision framework. Results show that the distributed mimic decision framework is efficient in decision-making and has flexible scalability.

Key words： mimic defense single decision unit distributed mimic decision triple modular redundancy voting model cascading topology fault tolerance

Received: 13 September 2024 Published: 27 October 2025

CLC:

TN 915.08

Fund: 国家重点研发计划资助项目（2022YFB3104300）.

	Service
	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Xinsheng YU
	Lunhan LUO
	Fan ZHANG
	Bo ZHANG
	Danjiang ZHU
	Wei XIE

Cite this article:

Xinsheng YU,Lunhan LUO,Fan ZHANG,Bo ZHANG,Danjiang ZHU,Wei XIE. Distributed mimic decision model and framework design. Journal of ZheJiang University (Engineering Science), 2025, 59(10): 2195-2204.

URL:

https://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2025.10.020 OR https://www.zjujournals.com/eng/Y2025/V59/I10/2195

分布式拟态裁决模型与架构设计

单裁决器拟态防御架构根据执行体数量预设裁决算法，导致执行体数量无法弹性伸缩，为此提出分布式拟态裁决模型，将执行体值裁决转变为多层级联逻辑运算的拓扑结构规划问题. 所提模型支持自定义数量的执行体与故障容许度，动态调整逻辑运算级联拓扑，解耦执行体数量与裁决算法的强一致性关系，移除根据执行体数量预设裁决算法的前提条件. 设计针对高安全、高鲁棒系统的分布式拟态裁决架构，定量分析执行体数量、容许度与级联逻辑运算迭代层数的关系. 在仿真实验中，对比单裁决器拟态裁决架构、经典三模冗余投票模型、分布式拟态裁决架构的裁决能力与裁决效率. 验证结果表明，分布式拟态裁决架构的裁决效率高，具有灵活的扩展性.

关键词： 拟态防御, 单裁决器, 分布式拟态裁决, 三模冗余投票模型, 级联拓扑, 故障容许度

Fig.1 N-candidate decision model

Fig.2 N–1-candidate decision model

Fig.3 Classical triple modular redundancy voting model

Tab.1 Values of classical triple modular redundancy voting model

Fig.4 Distributed mimic decision model

Fig.5 Mimic decision framework for high-security information system including four executors

Fig.6 Judgement in decision unit of information system including four executors

Fig.7 Cascading topology for judge layer 2

Fig.8 Cascading topology for improving computational efficiency of judge layer 2

Fig.9 Logical operation units in judge layer 2 （four executors, one fault tolerance information system）

Fig.10 Logical operation units in judge layer 2（n executors, r fault tolerance information system）

Fig.11 Mimic decision framework for high-robustness information system (four executors, one fault tolerance information system)

Fig.12 Schematic diagrams of different mimic decision frameworks (three executors, zero fault tolerance information system)

Fig.13 Decision intervals for different mimic decision frameworks (three executors, zero fault tolerance information system)

Tab.2 Decision results of different mimic decision frameworks (three executors, zero fault tolerance information system)

Fig.14 Schematic diagrams of different mimic decision frameworks (four executors, one fault tolerance information system)

Fig.15 Decision intervals for different mimic decision frameworks (four executors, one fault tolerance information system)

Tab.3 Decision results of different mimic decision frameworks (four executors, one fault tolerance information system)

Fig.16 Decision intervals for different mimic decision frameworks (five executors, two fault tolerance information system)

Tab.4 Decision intervals of distributed mimic decision frames (n executors, r fault tolerance information system)


[1]	邬江兴网络空间拟态安全防御[J]. 保密科学技术, 2014, (10): 4- 9 WU Jiangxing Cyber mimic defense[J]. Secrecy Science and Technology, 2014, (10): 4- 9

[2]	罗兴国, 仝青, 张铮, 等拟态防御技术[J]. 中国工程科学, 2016, 18 (6): 69- 73 LUO Xingguo, TONG Qing, ZHANG Zheng, et al Mimic defense technology[J]. Strategic Study of CAE, 2016, 18 (6): 69- 73 doi: 10.15302/J-SSCAE-2016.06.014

[3]	邬江兴网络空间拟态防御研究[J]. 信息安全学报, 2016, 1 (4): 1- 10 WU Jiangxing Research on cyber mimic defense[J]. Journal of Cyber Security, 2016, 1 (4): 1- 10

[4]	仝青, 张铮, 邬江兴基于软硬件多样性的主动防御技术[J]. 信息安全学报, 2017, 2 (1): 1- 12 TONG Qing, ZHANG Zheng, WU Jiangxing The active defense technology based on the software/hardware diversity[J]. Journal of Cyber Security, 2017, 2 (1): 1- 12

[5]	LEVITIN G Optimal structure of fault-tolerant software systems[J]. Reliability Engineering and System Safety, 2005, 89 (3): 286- 295 doi: 10.1016/j.ress.2004.09.001

[6]	LATIF-SHABGAHI G, BENNETT S. Adaptive majority voter: a novel voting algorithm for real-time fault-tolerant control systems [C]// Proceedings 25th EUROMICRO Conference. Milan: IEEE, 1999: 113–120.

[7]	CONITZER V, SANDHOLM T. Common voting rules as maximum likelihood estimators [C]// Proceedings of the Twenty-First Conference on Uncertainty in Artificial Intelligence. Edinburgh: ACM, 2005: 145–152.

[8]	杨晓晗, 程国振, 刘文彦, 等基于深度学习的拟态裁决方法研究[J]. 通信学报, 2024, 45 (2): 79- 89 YANG Xiaohan, CHENG Guozhen, LIU Wenyan, et al Research on mimic decision method based on deep learning[J]. Journal on Communications, 2024, 45 (2): 79- 89 doi: 10.11959/j.issn.1000-436x.2024047

[9]	高振斌, 贾广瑞, 张文建, 等基于异常值的拟态裁决优化方法[J]. 计算机应用研究, 2021, 38 (7): 2066- 2071 GAO Zhenbin, JIA Guangrui, ZHANG Wenjian, et al Mimic ruling optimization method based on executive outliers[J]. Application Research of Computers, 2021, 38 (7): 2066- 2071

[10]	LATIF-SHABGAHI G, BASS J M, BENNETT S. History-based weighted average voter: a novel software voting algorithm for fault-tolerant computer systems [C]// Proceedings Ninth Euromicro Workshop on Parallel and Distributed Processing. Mantova: IEEE, 2001: 402–409.

[11]	武兆琪, 张帆, 郭威, 等一种基于执行体异构度的拟态裁决优化方法[J]. 计算机工程, 2020, 46 (5): 12- 18 WU Zhaoqi, ZHANG Fan, GUO Wei, et al A mimic arbitration optimization method based on heterogeneous degree of executors[J]. Computer Engineering, 2020, 46 (5): 12- 18

[12]	宋克, 欧阳玲, 张文建, 等一种软硬件协同的拟态调度裁决器设计方法[J]. 信息工程大学学报, 2020, 21 (5): 593- 600 SONG Ke, OUYANG Ling, ZHANG Wenjian, et al Design method of mimic scheduling adjudicator based on hardware and software collaboration[J]. Journal of Information Engineering University, 2020, 21 (5): 593- 600

[13]	普黎明, 柏溢, 游伟, 等面向拟态云服务的异构执行体输出裁决方法[J]. 信息工程大学学报, 2020, 21 (3): 344- 351 PU Liming, BAI Yi, YOU Wei, et al Heterogeneous executors output decision method for mimic cloud service[J]. Journal of Information Engineering University, 2020, 21 (3): 344- 351 doi: 10.3969/j.issn.1671-0673.2020.03.015

[14]	FAZLALI M, MOAZEZI-EFTEKHAR S, DEHSHIBI M M, et al. Raft consensus algorithm: an effective substitute for Paxos in high throughput P2P-based systems [EB/OL]. (2019–11–04)[2024–08–01]. https://arxiv.org/pdf/1911.01231.

[15]	DHARMAWARDENA P K, WANG Z Cluster head selection based routing protocol for VANET using bully algorithm and Lamport timestamp[J]. International Journal of Computer Theory and Engineering, 2017, 9 (3): 218- 222 doi: 10.7763/IJCTE.2017.V9.1141

[16]	RAMANI S, JHAVERI R H ML-based delay attack detection and isolation for fault-tolerant software-defined industrial networks[J]. Sensors, 2022, 22 (18): 6958 doi: 10.3390/s22186958

[17]	KOTACHI S, SATO T, SHINKUMA R, et al. Fault-tolerant controller placement model by distributing switch load among multiple controllers in software-defined network [J]. IEICE Transactions on Communications, 2022, E105. B(5): 533–544.

[18]	NODA S, SATO T, OKI E. Fault-tolerant controller placement model based on load-dependent sojourn time in software-defined network [C]// Proceedings of the IEEE 8th International Conference on Network Softwarization. Milan: IEEE, 2022: 393–401.

[19]	KILLI B P R, RAO S V Towards improving resilience of controller placement with minimum backup capacity in software defined networks[J]. Computer Networks, 2019, 149: 102- 114 doi: 10.1016/j.comnet.2018.11.027

[20]	SRIDHARAN V, GURUSAMY M, TRUONG-HUU T On multiple controller mapping in software defined networks with resilience constraints[J]. IEEE Communications Letters, 2017, 21 (8): 1763- 1766 doi: 10.1109/LCOMM.2017.2696006

[1]	Guang-xuan LIU,Shan HUANG,Jia-li HU,Xiao-dong DUAN. Fault tolerant optimization of active backup for Flink stream processing framework[J]. Journal of ZheJiang University (Engineering Science), 2022, 56(2): 297-305.

[2]	Lei ZHANG,Jing ZHANG. Differential privacy protection scheme supporting high data utility and fault tolerance[J]. Journal of ZheJiang University (Engineering Science), 2019, 53(8): 1496-1505.

[3]	WANG Kai, YUE Bo-xuan, FU Jun-wei, LIANG Jun. Image restoration and fault tolerance of stereo SLAM based on generative adversarial net[J]. Journal of ZheJiang University (Engineering Science), 2019, 53(1): 115-125.

[4]	QI Xiao-gang, WANG Zhen-yu, LIU Li-fang, LIU Xing-cheng, MA Jiu-long. Reliable and efficient routing of wireless sensors and actuator networks[J]. Journal of ZheJiang University (Engineering Science), 2018, 52(10): 1964-1972.

Viewed

Full text

Abstract

Cited

Shared

Discussed