This paper focuses on secure consensus for leader-following multiagent systems (MASs) modeled by partial differential equations (PDEs) under denial of service (DoS) attacks. To mitigate the negative effects of DoS attacks, which can paralyze communication and cause agents to fail to receive valid control inputs, a buffer region is established in the communication channels among agents to temporarily store messages from neighbors. Additionally, since the states of the leader and followers are not always measurable, observers are used to estimate these states. To address these challenges, this paper proposes two boundary controllers to ensure leader-following consensus in both measurable and unmeasurable states. One controller is based on original boundary information, while the other utilizes observation information from both the leader and followers. To the best of our knowledge, this is the first attempt to use buffers to solve a class of PDEs-based MASs under DoS attacks. Furthermore, the boundary control approach has the potential to significantly reduce the number of actuators required, thereby lowering control costs. Finally, we present two numerical examples to validate the feasibility of the proposed methods.
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http://dx.doi.org/10.1016/j.isatra.2024.08.014 | DOI Listing |
ISA Trans
December 2024
School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China. Electronic address:
Denial-of-service (DoS) attacks and antagonistic interactions may exist in complex networks, which will destroy cooperative communication between agents and thus cannot realize collaborative tasks. Therefore, this paper studies time-varying formation tracking (TVFT) of heterogeneous multi-agent systems (HMASs) with DoS attacks and cooperative-antagonistic interactions. It aims to ensure system communication connectivity and allow followers to achieve distributed secure bipartite TVFT.
View Article and Find Full Text PDFPLoS One
December 2024
RIOTU Lab, CCIS, Prince Sultan University, Riyadh, Saudi Arabia.
Vehicular Networks (VN) utilizing Software Defined Networking (SDN) have garnered significant attention recently, paralleling the advancements in wireless networks. VN are deployed to optimize traffic flow, enhance the driving experience, and ensure road safety. However, VN are vulnerable to Distributed Denial of Service (DDoS) attacks, posing severe threats in the contemporary Internet landscape.
View Article and Find Full Text PDFNeotrop Entomol
December 2024
Programa de Pós-Graduação Em Produção Vegetal, Univ Federal Dos Vales Jequitinhonha E Mucuri, Diamantina, MG, Brazil.
Neural Netw
December 2024
School of Mathematical Science, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan, China. Electronic address:
This article is concerned with the deterministic finite automaton-mode-dependent (DFAMD) exponential stability problem of impulsive switched memristive neural networks (SMNNs) with aperiodic asynchronous attacks and the network covert channel. First, unlike the existing literature on SMNNs, this article focuses on DFA to drive mode switching, which facilitates precise system behavior modeling based on deterministic rules and input characters. To eliminate the periodicity and consistency constraints of traditional attacks, this article presents the multichannel aperiodic asynchronous denial-of-service (DoS) attacks, allowing for the diversity of attack sequences.
View Article and Find Full Text PDFSensors (Basel)
November 2024
SMART Technology Research Centre, Department of Cyber Security and Networks, School of Computing, Engineering and Built Environment, Glasgow Caledonian University, Glasgow G4 0BA, UK.
IoT devices with limited resources, and in the absence of gateways, become vulnerable to various attacks, such as denial of service (DoS) and man-in-the-middle (MITM) attacks. Intrusion detection systems (IDS) are designed to detect and respond to these threats in IoT environments. While machine learning-based IDS have typically been deployed at the edge (gateways) or in the cloud, in the absence of gateways, the IDS must be embedded within the sensor nodes themselves.
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