基于隐写术的分布式隐私保护一致性控制方法

伍益明; 张润荣; 徐宏; 朱晨睿; 郑宁

doi:10.16383/j.aas.c240089

基于隐写术的分布式隐私保护一致性控制方法

doi: 10.16383/j.aas.c240089

伍益明^1,,
张润荣^1,,
徐宏^{2, 3,},
朱晨睿^{1, 3,},
郑宁^1,

1.
杭州电子科技大学网络空间安全学院杭州 310018
2.
杭州电子科技大学计算机学院杭州 310018
3.
中国电子科技集团公司第三十二研究所上海 201800

基金项目: 浙江省公益技术应用研究项目(LGF21F020011)资助

详细信息

作者简介:
伍益明：杭州电子科技大学网络空间安全学院副教授. 主要研究方向网络安全, 分布式系统安全控制, 集群智能. 本文通信作者. E-mail: ymwu@hdu.edu.cn

张润荣：杭州电子科技大学网络空间安全学院硕士研究生. 主要研究方向为多智能体系统网络安全, 隐私保护. E-mail: 212270030@hdu.edu.cn

徐宏：中国电子科技集团公司第三十二研究所高级工程师. 杭州电子科技大学计算机学院博士研究生. 主要研究方向为计算机软件架构, 信号处理和群体机器人技术. E-mail: frankxuh@126.com

朱晨睿：杭州电子科技大学网络空间安全学院博士研究生. 主要研究方向为无人集群, 边缘计算和资源调度. E-mail: zzzcr2022@gmail.com

郑宁：杭州电子科技大学网络空间安全学院研究员. 主要研究方向包括信息安全和信息管理系统. E-mail: nzheng@hdu.edu.cn

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出版历程
- 收稿日期: 2024-02-23
- 录用日期: 2024-08-27
- 网络出版日期: 2024-09-10

Distributed Privacy-preserving Consensus Control Based on Steganography

WU Yi-Ming^1
,,
ZHANG Run-Rong^1
,,
XU Hong^{2, 3
,},
ZHU Chen-Rui^{1, 3
,},
ZHENG Ning^1
,

1.
School of Cyberspace, Hangzhou Dianzi University, Hangzhou 310018
2.
School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018
3.
The 32nd Research Institute of China Electronics Technology Group Corporation, Shanghai 201800

Funds: Supported by Zhejiang Provincial Public Welfare Research Project of China (LGF21F020011)

More Information

Author Bio:
WU Yi-Ming　Associate professor at the School of Cyberspace, Hangzhou Dianzi University. His research interest covers cyber security, distributed system secure control, and swarm intelligence. Corresponding author of this paper

ZHANG Run-Rong　Master student at the School of Cyberspace, Hangzhou Dianzi University. Her research interest covers cyber security for multi-agent systems and privacy-preserving

XU Hong　Senior engineer at the 32nd Research Institute of China Electronics Technology Group Corporation. Ph.D. candidate at the School of Computer Science and Technology, Hangzhou Dianzi University. His research interest covers computer software architecture, signal processing and swarm robotics

ZHU Chen-Rui　Ph.D. candidate at the School of Cyberspace, Hangzhou Dianzi University. His research interest covers UAV swarm, edge computing, and resource scheduling

ZHENG Ning　Professor at the School of Cyberspace, Hangzhou Dianzi University. His research interest covers information security and information management systems

摘要

摘要: 多智能体网络(Multi-agent network, MAN)协同执行任务中需要个体之间频繁交换并共享信息, 这对网络安全带来了巨大风险. 考虑网络中节点状态隐私保护问题, 提出一种基于隐写术的分布式一致性控制策略. 首先, 建立网络窃听者攻击模型, 提出面向隐私保护的分布式平均一致性控制算法. 理论分析表明, 所提算法不仅有效保护节点初始状态的隐私, 而且可以通过隐写载体信息主动诱导窃听者推测得出错误结论. 其次, 通过引入概率指标, 提出一种用于量化MAN隐私泄露指标模型, 实现了对网络隐私泄露程度的准确描述. 并基于该模型, 从窃听者视角, 通过权衡对网络隐私泄露的影响与付出代价成本建立一个优化问题, 据此寻找最优效益攻击策略. 最后, 通过数值仿真分析, 对比现有算法验证了所提方法的有效性和优越性.
- 多智能体网络 /
- 隐私保护 /
- 窃听攻击 /
- 网络安全 /
- 隐写术
Abstract: Multi-agent network (MAN) requires frequent exchange and sharing of information among individuals in collaborative task execution, which poses significant risks to network security. To address the issue of privacy protection of node states in the network, a distributed consensus control strategy based on steganography is proposed. Firstly, an eavesdropper attack model is established, and a distributed privacy-preserving average consensus control algorithm is proposed. Theoretical analysis shows that the proposed algorithm not only effectively protects the privacy of node initial states but also can actively lead eavesdroppers to draw incorrect conclusions through steganographic carrier information. Secondly, a probabilistic indicator is introduced to quantify the privacy leakage index model for MAN, achieving an accurate description of the degree of network privacy leakage. Based on this model, an optimization problem is established from the eavesdropper's perspective by balancing the impact on network privacy leakage and the cost of attack, in order to find the optimal benefit attack strategy. Finally, through numerical simulation, the effectiveness and superiority of the proposed method are verified by comparing with existing algorithms.
- Multi-agent network (MAN) /
- privacy-preserving /
- eavesdropping attack /
- network security /
- steganography

HTML全文

图 1 基于隐写术的一致性算法示意图

Fig. 1 Schematic diagram of consensus algorithm based on steganography

下载: 全尺寸图片幻灯片

图 2 5个节点组成的MAN通信图

Fig. 2 Communication graph of MAN with 5 nodes

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图 3 实例中5个节点的真实状态值和虚假状态值轨迹变化曲线

Fig. 3 The trajectory curves of the real and fake state value of 5 nodes in the instance

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图 4 窃听者对采用文献[5]算法的节点$ v_2$初始状态值的观测结果

Fig. 4 The observation results of eavesdropper on the initial value of node $ v_2$ using the algorithm in [5]

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图 5 窃听者对采用本文算法的节点$v_2$初始状态值的观测结果

Fig. 5 The observation results of eavesdropper on the initial state value of node $v_2$ using the algorithm proposed in this paper

下载: 全尺寸图片幻灯片

参考文献(30)

[1]	Zhao J, Zhu K, Hu H, et al. Formation control of networked mobile robots with unknown reference orientation. IEEE/ASME Transactions on Mechatronics, 2023, 28(4): 2200−2212 doi: 10.1109/TMECH.2022.3231079
[2]	Gough M B, Santos S F, AlSkaif T, Javadi M S, Castro R, Catalao J P S. Preserving privacy of smart meter data in a smart grid environment. IEEE Transactions on Industrial Informatics, 2021, 18(1): 707−718
[3]	Dong X, Hu G. Time-varying output formation for linear multiagent systems via dynamic output feedback control. IEEE Transactions on Control of Network Systems, 2017, 4(2): 236−245 doi: 10.1109/TCNS.2015.2489358
[4]	Xiao N, Wang X, Xie L, Wongpiromsarn Ti, Frazzoli E, Rus D. Road pricing design based on game theory and multi-agent consensus. IEEE/CAA Journal of Automatica Sinica, 2014, 1(1): 31−39 doi: 10.1109/JAS.2014.7004617
[5]	Mo Y, Murray R M. Privacy preserving average consensus. IEEE Transactions on Automatic Control, 2017, 62(2): 753−765 doi: 10.1109/TAC.2016.2564339
[6]	Qin J, Ma Q, Shi Y, Wang L. Recent advances in consensus of multi-agent systems: A brief survey. IEEE Transactions on Industrial Electronics, 2017, 64(6): 4972−4983 doi: 10.1109/TIE.2016.2636810
[7]	朱静, 王飞跃, 王戈, 田永林, 袁勇, 王晓, 等. 联邦控制: 面向信息安全和权益保护的分布式控制方法. 自动化学报, 2021, 47(8): 1912−1920 Zhu Jing, Wang Fei-Yue, Wang Ge, Tian Yong-Lin, Yuan Yong, Wang Xiao, et al. Federated control: A distributed control approach towards information security and rights protection. Acta Automatica Sinica, 2021, 47(8): 1912−1920
[8]	应晨铎, 伍益明, 徐明, 郑宁, 何熊熊. 欺骗攻击下具备隐私保护的多智能体系统均值趋同控制. 自动化学报, 2023, 49(2): 425−436 Ying Chen-Duo, Wu Yi-Ming, Xu Ming, Zheng Ning, He Xiong-Xiong. Privacy-preserving average consensus control formulti-agent systems under deception attacks. Acta Automatica Sinica, 2023, 49(2): 425−436
[9]	Wang Y, Lu J, Zheng W X, Shi K. Privacy-preserving consensus for multi-agent systems via node decomposition strategy. IEEE Transactions on Circuits and Systems I: Regular Papers, 2021, 68(8): 3474−3484 doi: 10.1109/TCSI.2021.3081372
[10]	Gao L, Deng S, Ren W. Differentially private consensus with an event-triggered mechanism. IEEE Transactions on Control of Network Systems, 2019, 6(1): 60−71 doi: 10.1109/TCNS.2018.2795703
[11]	Liu X.-K, Zhang J.-F, Wang J. Differentially private consensus algorithm for continuous-time heterogeneous multi-agent systems. Automatica, 2020, 12: 109283
[12]	He J, Cai L, Cheng P, Pan J, Shi L. Consensus-based data-privacy preserving data aggregation. IEEE Transactions on Automatic Control, 2019, 64(12): 5222−5229 doi: 10.1109/TAC.2019.2910171
[13]	Zhao C, Chen J, He J, Cheng P. Privacy-preserving consensus-based energy management in smart grids. IEEE Transactions on Signal Processing, 2018, 66(23): 6162−6176 doi: 10.1109/TSP.2018.2872817
[14]	Pan D, Ding D, Ge X, Han Q L, Zhang X M. Privacy-preserving platooning control of vehicular cyber-physical systems with saturated inputs. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, 53(4): 2083−2097 doi: 10.1109/TSMC.2022.3226901
[15]	Gao C, Wang Z, He X, Dong H. Fault-tolerant consensus control for multiagent systems: An encryption-decryption scheme. IEEE Transactions on Automatic Control, 2022, 67(5): 2560−2567 doi: 10.1109/TAC.2021.3079407
[16]	Hadjicostis C N. Privary preserving distributed average consensus via homomorphic encryption. In: Proceedings of the IEEE Conference on Decision and Control (CDC). Miami, USA: IEEE, 2018. 1258-1263
[17]	Lee K, Hong J -P, Choi H -H, Levorato M. Adaptive wireless-powered relaying schemes with cooperative jamming for two-hop secure communication. IEEE Internet of Things Journal, 2018, 5(4): 2793−2803 doi: 10.1109/JIOT.2018.2830880
[18]	Wang Y. Privacy-preserving average consensus via state decomposition. IEEE Transactions on Automatic Control, 2019, 64(11): 4711−4716 doi: 10.1109/TAC.2019.2902731
[19]	Chen X, Huang L, Ding K, Dey S, Shi L. Privacy-preserving push-sum average consensus via state decomposition. IEEE Transactions on Automatic Control, 2023, 68(12): 7974−7981 doi: 10.1109/TAC.2023.3256479
[20]	Zhang J, Lu J, Chen X. Privacy-preserving average consensus via edge decomposition. IEEE Control Systems Letters, 2022, 6: 2503−2508 doi: 10.1109/LCSYS.2022.3166759
[21]	Anderson R J, Petitcolas F A P. On the limits of steganography. IEEE Journal on Selected Areas in Communications, 1998, 16(4): 474−481 doi: 10.1109/49.668971
[22]	Wang Z, Byrnes O, Wang H, Sun R, Ma C, Chen H, et al. Data hiding with deep learning: A survey unifying digital watermarking and steganography. IEEE Transactions on Computational Social Systems, 2023, 10(6): 2985−2999 doi: 10.1109/TCSS.2023.3268950
[23]	Mazurczyk W, Caviglione L. Steganography in modern smartphones and mitigation techniques. IEEE Communications Surveys & Tutorials, 2015, 17(1): 334−357
[24]	沈昌祥, 张焕国, 冯登国, 曹珍富, 黄继武. 信息安全综述. 中国科学E辑, 2007, 37(2): 129−150 Shen Chang-Xiang, Zhang Huan-Guo, Feng Deng-Guo, Cao Zhen-Fu, Huang Ji-Wu. Overview of information security. Science in China (Series E), 2007, 37(2): 129−150
[25]	Xiao X, Sun X, Yang L, Chen M. Secure data transmission of wireless sensor network based on information hiding. In: Proceedings of the 4th Annual International Conference on Mobile and Ubiquitous Systems: Networking & Services. Philadelphia, USA: IEEE, 2007. 1−6
[26]	Olfati-Saber R, Fax J A, Murray R. Consensus and cooperation in networked multi-agent systems. Proceedings of the IEEE, 2007, 95(1): 215−233 doi: 10.1109/JPROC.2006.887293
[27]	Zhao B, Zhang Y. Secure encoding strategy for consensus of multi-agent systems in the presence of eavesdropper. IEEE Transactions on Circuits and Systems II: Express Briefs, 2022, 69(8): 3420−3424
[28]	Wang A, Liu W, Li T, Huang T. Privacy-preserving weighted average consensus and optimal attacking strategy for multi-agent networks. Journal of the Franklin Institute, 2021, 358(6): 3033−3050 doi: 10.1016/j.jfranklin.2021.01.039
[29]	Charalambous T, Manitara N E, Hadjicostis C N. Privacy-preserving average consensus over digraphs in the presence of time delays. In: Proceedings of the 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton). Monticello, USA: IEEE, 2019. 238−245
[30]	Manitara N E, Rikos A I, Hadjicostis C N. Privacy-preserving distributed average consensus in finite time using random gossip. In: Proceedings of the 2022 European Control Conference (ECC). London, UK: IEEE, 2022. 1282−1287