Survey of Recent Results in Privacy-Preserving Mechanisms for Multi-Agent Systems

被引:0
|
作者
Kossek, Magdalena [1 ]
Stefanovic, Margareta [1 ]
机构
[1] Univ Denver, Daniel Felix Ritchie Sch Engn & Comp Sci, 2155 E Wesley Ave, Denver, CO 80208 USA
关键词
Multi-agent systems; Privacy preserving control; Formation control; Signal obfuscation; Differential privacy; Encryption-based privacy; FOLLOWER FORMATION CONTROL; DYNAMIC AVERAGE CONSENSUS; MARINE SURFACE VEHICLES; AUTHENTICATION; ALGORITHM; FRAMEWORK; TRACKING; SCHEME; SECURE; TIME;
D O I
10.1007/s10846-024-02161-9
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Privacy-preserving communication in cooperative control is essential for effective operations of various systems where sensitive information needs to be protected. This includes systems such as smart grids, traffic management systems, autonomous vehicle networks, healthcare systems, financial networks, and social networks. Recent privacy-preserving cooperative control literature is categorized and discussed in this paper. Advantages and disadvantages of differential privacy and encryption-based privacy-preserving protocols are described. The objective of this work is to examine and analyze existing research and knowledge related to the preservation of privacy in the context of cooperative control. This paper aims to identify and present a range of approaches, techniques, and methodologies that have been proposed or employed to address privacy concerns in multi-agent systems. It seeks to explore the current challenges, limitations, and gaps in the existing literature. It also aims to consolidate the findings from various studies to provide an overview of privacy-preserving cooperative control in multi-agent systems. The goal is to assist in the development of novel privacy-preserving mechanisms for cooperative control.
引用
收藏
页数:27
相关论文
共 50 条
  • [41] A survey of privacy-preserving mechanisms for heterogeneous data types
    Cunha, Mariana
    Mendes, Ricardo
    Vilela, Joao P.
    COMPUTER SCIENCE REVIEW, 2021, 41
  • [42] A Survey on Location Privacy-Preserving Mechanisms in Mobile Crowdsourcing
    Bashanfar, Arwa
    Al-Zahrani, Eman
    Alutebei, Maram
    Aljagthami, Wejdan
    Alshehri, Suhari
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2019, 10 (07) : 626 - 632
  • [43] Privacy-Preserving Mechanisms for Crowdsensing: Survey and Research Challenges
    Vergara-Laurens, Idalides J.
    Jaimes, Luis G.
    Labrador, Miguel A.
    IEEE INTERNET OF THINGS JOURNAL, 2017, 4 (04): : 855 - 869
  • [44] Mechanisms for environments in multi-agent systems: Survey and opportunities
    Platon, Eric
    Mamei, Marco
    Sabouret, Nicolas
    Honiden, Shinichi
    Van Dyke Parunak, H.
    AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS, 2007, 14 (01) : 31 - 47
  • [45] Mechanisms for environments in multi-agent systems: Survey and opportunities
    Eric Platon
    Marco Mamei
    Nicolas Sabouret
    Shinichi Honiden
    H. Van Dyke Parunak
    Autonomous Agents and Multi-Agent Systems, 2007, 14 : 31 - 47
  • [46] Distributed event-triggered-based encrypted control for nonlinear multi-agent systems via privacy-preserving approach
    Wang, Shuailong
    Liu, Jian
    Zha, Lijuan
    Liu, Jinliang
    NONLINEAR DYNAMICS, 2025, 113 (09) : 10127 - 10142
  • [47] Finite-Time Privacy-Preserving Average Consensus Control of Multi-Agent Systems Via Output Mask Approach
    Yue, Jiangfeng
    Li, Weihao
    Shi, Mengji
    Li, Tong
    Lin, Boxian
    Qin, Kaiyu
    2023 35TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC, 2023, : 2670 - 2675
  • [48] Asymmetric bipartite consensus for multi-agent systems with strong-privacy-preserving
    Fang, Fan
    Yang, Hongyong
    Liu, Fei
    IET CONTROL THEORY AND APPLICATIONS, 2024, 18 (12): : 1569 - 1585
  • [49] Privacy preserving distributed event-triggered optimisation for multi-agent systems
    Zhao, Zhongyuan
    Yang, Zhiqiang
    Ji, Qiutong
    INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2024, 55 (15) : 3155 - 3165
  • [50] Collaborative privacy preserving multi-agent planningPlanners and heuristics
    Shlomi Maliah
    Guy Shani
    Roni Stern
    Autonomous Agents and Multi-Agent Systems, 2017, 31 : 493 - 530