Protocol-Based Distributed Security Fusion Estimation for Time-Varying Uncertain Systems Over Sensor Networks: Tackling DoS Attacks

IF 3 3区计算机科学 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Transactions on Signal and Information Processing over Networks Pub Date : 2024-01-22 DOI:10.1109/TSIPN.2024.3356789

Lijuan Zha;Yaping Guo;Jinliang Liu;Xiangpeng Xie;Engang Tian

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引用次数: 0

Abstract

This article studies the distributed fusion estimation (DFE) issue for networked multi-sensor systems (NMSSs) with stochastic uncertainties, bandwidth-constrained network and energy-constrained denial-of-service (DoS) attacks. The stochastic uncertainties reflected in both the state and measurement models are characterized by multiplicative noises. For reducing the communication burden, local estimation signals are subject to dimensionality reduction processing. And the improved Round-Robin (RR) protocol is used on the channels from local estimators to the fusion estimator. To reflect the actual situation, the dimensionality reduction strategy is designed from the defender's point of view in the sense of minimum fusion error covariance (FEC). And the attack strategy is designed from the attacker's point of view in the sense of maximum FEC. Then, based on a compensation model, a recursive distributed Kalman fusion estimation algorithm (DKFEA) is proposed. The stability conditions making the mean square error (MSE) for DFE bounded are derived. In the end, the validity of the presented DKFEA is verified by an illustrative example.

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基于协议的传感器网络时变不确定系统分布式安全融合估计：应对 DoS 攻击

本文研究了具有随机不确定性、带宽受限网络和能量受限拒绝服务（DoS）攻击的联网多传感器系统（NMSS）的分布式融合估计（DFE）问题。状态和测量模型中反映的随机不确定性具有乘法噪声的特征。为了减轻通信负担，局部估计信号需要进行降维处理。从局部估计器到融合估计器的信道采用改进的循环（RR）协议。为了反映实际情况，从防御方的角度出发，设计了最小融合误差协方差（FEC）的降维策略。而攻击策略则从攻击者的角度出发，从最大 FEC 的意义上进行设计。然后，基于补偿模型，提出了递归分布式卡尔曼融合估计算法（DKFEA）。推导出了使 DFE 均方误差（MSE）有界的稳定性条件。最后，通过一个示例验证了所提出的 DKFEA 的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Signal and Information Processing over Networks Computer Science-Computer Networks and Communications

CiteScore

5.80

自引率

12.50%

发文量

期刊介绍： The IEEE Transactions on Signal and Information Processing over Networks publishes high-quality papers that extend the classical notions of processing of signals defined over vector spaces (e.g. time and space) to processing of signals and information (data) defined over networks, potentially dynamically varying. In signal processing over networks, the topology of the network may define structural relationships in the data, or may constrain processing of the data. Topics include distributed algorithms for filtering, detection, estimation, adaptation and learning, model selection, data fusion, and diffusion or evolution of information over such networks, and applications of distributed signal processing.