Deception Attacks Research Articles

Adaptive Event-Triggered Consensus Control for Nonlinear Multiagent Systems Against Deception Attacks

Adaptive Event-Triggered Consensus Control for Nonlinear Multiagent Systems Against Deception Attacks

State-Observer-Based Event-Trigger Bipartite Consensus Secure Control for NMASs with Deception Attacks

State-Observer-Based Event-Trigger Bipartite Consensus Secure Control for NMASs with Deception Attacks

Event-Based Secure State Estimation for 2-D CPSs Under Deception Attacks: A Game Theoretic Approach

Event-Based Secure State Estimation for 2-D CPSs Under Deception Attacks: A Game Theoretic Approach

Bipartite Leader-Following Consensus of Multiagent Systems on Switching Signed Networks Under Deception Attacks and Its Application to Image Communication

Bipartite Leader-Following Consensus of Multiagent Systems on Switching Signed Networks Under Deception Attacks and Its Application to Image Communication

Design of Linear Deception Attacks Against State Estimation in Multi-plant Power Systems

Design of Linear Deception Attacks Against State Estimation in Multi-plant Power Systems

Event-Triggered Security Control for Connected Vehicle Platoon System Subject to Deception Attacks

Event-Triggered Security Control for Connected Vehicle Platoon System Subject to Deception Attacks

Event-Triggered Impulsive Control for Complex Networks Under Stochastic Deception Attacks

Event-Triggered Impulsive Control for Complex Networks Under Stochastic Deception Attacks

Adaptive Impulsive Consensus of Nonlinear Multiagent Systems With Limited Bandwidth Under Uncertain Deception Attacks

Adaptive Impulsive Consensus of Nonlinear Multiagent Systems With Limited Bandwidth Under Uncertain Deception Attacks

Anti-Watermarking Stealthy Deception Attacks Against Networked Unmanned Surface Vehicles

Anti-Watermarking Stealthy Deception Attacks Against Networked Unmanned Surface Vehicles

Adaptive Neural Sliding-Mode Control for Fuzzy Singularly Perturbed Systems: Sojourn-Probability-Based Stochastic Communication Protocol.

This article addresses an adaptive neural network (NN) sliding-mode control (SMC) strategy for fuzzy singularly perturbed systems against unrestricted deception attacks and stochastic communication protocol (SCP). Instead of relying on the traditional transition probability, a sojourn-probability-based SCP is efficiently established to characterize the stochastic nature more precisely. In response to unrestricted deception attacks, an NN-based technique is deployed to estimate and counteract their detrimental impacts on system performance. Moreover, the design of the sliding-mode controller integrates the singular perturbation parameter and fuzzy rules, addressing the challenge of imperfect premise matching. The proposed controller guarantees exponential ultimate boundedness in the mean square sense and ensures the reachability of the specified sliding surface for the closed-loop system. Finally, the efficacy of the proposed theoretical framework is validated through two illustrative examples, confirming its practical applicability and robustness.

Adaptive Intelligent Control for Nonlinear Stochastic Cyber-Physical Systems With Unknown Deception Attacks: Switching Event-Triggered Scheme

Adaptive Intelligent Control for Nonlinear Stochastic Cyber-Physical Systems With Unknown Deception Attacks: Switching Event-Triggered Scheme

Predictive Sliding-Mode Control for Networked High-Order Fully Actuated Multiagents Under Random Deception Attacks

Predictive Sliding-Mode Control for Networked High-Order Fully Actuated Multiagents Under Random Deception Attacks

Resilient Neural-Sliding-Mode Distance Regulation in Merging Control of Heterogeneous Connected Automated Vehicles Subject to Deception Attacks

Resilient Neural-Sliding-Mode Distance Regulation in Merging Control of Heterogeneous Connected Automated Vehicles Subject to Deception Attacks

Reliable Control of Wind Power Systems Under Frequency-Based Deception Attacks: AMD Event-Triggered Strategy

Reliable Control of Wind Power Systems Under Frequency-Based Deception Attacks: AMD Event-Triggered Strategy

Weight-Based Distributed Formation Control for Networked Marine Surface Vehicles With Hybrid Communication Channel Deception Attacks

Weight-Based Distributed Formation Control for Networked Marine Surface Vehicles With Hybrid Communication Channel Deception Attacks

Membership-Function-Dependent Reachable Set Synthesis of Takagi-Sugeno Fuzzy Singular Multi-Agent Systems Subject to Deception Attacks

Membership-Function-Dependent Reachable Set Synthesis of Takagi-Sugeno Fuzzy Singular Multi-Agent Systems Subject to Deception Attacks

DoS and Stealthy Deception Attacks for Switched Systems: A Cooperative Approach

DoS and Stealthy Deception Attacks for Switched Systems: A Cooperative Approach

Practical finite-time and fixed-time containment for second-order nonlinear multi-agent systems with IDAs and Markov switching topology

In this article, the finite-time containment problem and the fixed-time containment problem accompanied by injection and deception attacks (IDAs) and Markov switching topology for second-order nonlinear multi-agent systems (MASs) are investigated, respectively. By introducing a radial basis function neural network (RBFNN), the approximation property of radial basis neural networks is used to solve the unmeasurable difficulties of nonlinear functions and injection attacks. Finite-time and fixed-time distributed control protocols are proposed for switching topologies and attack-induced state deception and control injection, and finite-time and fixed-time containment as well as obtaining their corresponding sufficient conditions are achieved, respectively. Correspondingly, two examples are shown to demonstrate the feasibility of the control protocols.

Sampled-based adaptive event-triggered resilient control for multiagent systems with hybrid cyber-attacks

The multiagent systems have shared broad application in many practical systems including unmanned aircraft clusters, intelligent robots, and intelligent transportation. However, many unexpected cyber-attacks may disturb or disrupt the normal communication of the agents, thus reducing the interacting efficiency of multiagent systems. Ever since the cyber-attacks have been proposed, the resilient control problem for multiagent systems has been intensively explored in light of the communication network growth. However, most of the consequences only focused on denial-of-service (DoS) attacks or deception attacks independently. Distinguished from the existing resilient control mechanisms, the current investigation represents the first attempt at designing an adaptive resilient controller for multiagent systems according to the sampled-based adaptive event-triggered manner, where denial-of-service (DoS) attacks and deception attacks are both considered. First, the hybrid cyber-attacks model and its impact on the closed-loop system are addressed. And then, an adaptive event-triggered strategy is proposed to reduce network resource consumption and ease the communication burden, where the designed adaptive law can automatically adjust the triggering threshold. Finally, the consensus state of multiagent systems is capable of achieving via a series of reasonable control rules formulated through Lyapunov functional approach despite suffering hybrid cyber-attacks. And a simulation example is given to substantiate the feasibility of the proposed method.

Dynamic memory-event-triggered consensus of uncertain MASs with networked attacks and delays

This paper addresses the problem of achieving consensus in leader-following multi-agent systems under event-triggered control, with considerations of model uncertainties, network time-delay, and random deception attacks. To address the challenges of limited network resources, we propose a novel event-triggered control scheme that employs a dynamic memory-based approach. The proposed scheme utilizes multiple historic event-triggered states that are correlated with the states of neighboring agents and the leader, and the threshold parameter varies dynamically with time. We establish a memory-based closed-loop system that considers both network delays and deception attacks. Using the Lyapunov stability theory, a sufficient condition is derived to ensure consensus performance, and the desired controller gains and triggered matrices are obtained by solving linear matrix inequalities. Besides, we provide a comparative analysis of the memoryless dynamic event-triggered control. Finally, we validate the effectiveness of proposed approach with simulation results.