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IEEE Transactions on Cybernetics

Consensus Control of Multiagent Systems Under DoS Attacks: A Dynamic-Key-Based Secure Scheme

Yang Zhang, Lifeng Ma, Chen Gao

Published Feb 13, 2026• 0 citations
Publisher

Abstract

In this article, the secure consensus control problem is investigated for discrete-time multiagent systems (DTMASs) subjected to denial-of-service (DoS) attacks, where a model-free controller is proposed based on the Q-learning (QL) method. In an attack-free case, a dynamic decaying encryption key is designed to enable secure state transmission over communication channels through quantization-based encryption to prevent unauthorized access. Under DoS attacks, the system switches to a safe mode that partially halts communication, where the key transforms into a local scaling parameter to prevent quantizer saturation through dynamic expansion. The QL-driven algorithm is introduced to autonomously synthesize control gain matrices, without requiring system dynamics models. Moreover, sufficient conditions on the frequency and duration of DoS attacks are derived to ensure that the model-free controller guarantees consensus in DTMASs. Finally, simulation studies involving highly maneuverable aircraft technology vehicles (HiMATVs) are conducted, demonstrating that DTMASs equipped with the proposed approach exhibit significantly enhanced attack resistance compared to conventional methods.

DOI
10.1109/tcyb.2026.3651535

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In this article, the secure consensus control problem is investigated for discrete-time multiagent systems (DTMASs) subjected to denial-of-service (DoS) attacks, where a model-free controller is proposed based on the Q-learning (QL) method. In an attack-free case, a dynamic decaying encryption key is designed to enable secure state transmission over communication channels through quantization-based encryption to prevent unauthorized access. Under DoS attacks, the system switches to a safe mode that partially halts communication, where the key transforms into a local scaling parameter to prevent quantizer saturation through dynamic expansion. The QL-driven algorithm is introduced to autonomously synthesize control gain matrices, without requiring system dynamics models. Moreover, sufficient conditions on the frequency and duration of DoS attacks are derived to ensure that the model-free controller guarantees consensus in DTMASs. Finally, simulation studies involving highly maneuverable aircraft technology vehicles (HiMATVs) are conducted, demonstrating that DTMASs equipped with the proposed approach exhibit significantly enhanced attack resistance compared to conventional methods.
This paper presents a novel defense mechanism against Distributed Denial of Service (DDoS) attacks specifically tailored for Quantum Key Distribution (QKD) systems. The core claim is the design of a new distributed DDoS attack defense mechanism leveraging the inherent properties of QKD. The proposed mechanism constructs a distributed secure network based on the secure key transmission of QKD, effectively mitigating the impact of DDoS attacks. This approach enhances network security and reliability by exploiting the quantum nature of the key exchange process. The detailed formulation of the defense strategy, including key rate monitoring, redundancy management, and adaptive protocol switching, are presented. The proposed system aims to provide a robust defense against sophisticated DDoS attacks that target QKD systems, ensuring the continued confidentiality and integrity of key exchange. The system's architecture is outlined, and the mathematical models used for key rate analysis and attack mitigation are described. Finally, future research directions focusing on the integration of machine learning for dynamic threat detection are discussed.
A QKD network can be considered an add-on technology to a standard communication network that provides IT-secure cryptographic keys as a service. As a result, security challenges resulting in the suspension of functional work must be addressed. This study analyzes a Denial of Service (DoS) attack on the Key Management System (KMS), one of the critical components of the QKD network in charge of key management and key provisioning to authorized consumers. Through simulation methods performed in the QKDNetSim, we show that legitimate customers experience significantly worse service during an excessive DoS attack on KMS.
We consider a multiagent consensus problem in the presence of adversarial agents. The adversaries are able to listen to the interagent communications and try to estimate the state of the agents. The agents have a limited bit rate for communication and are required to quantize the transmitted signal in order to meet the bit rate constraint of the communication channel. We propose a consensus protocol that isprotectedagainst the adversaries, i.e., the expected mean-square error of the adversary state estimate is lower bounded. In order to deal with the bit rate constraint, we propose a dynamic quantization scheme that guaranteesprotected consensus.
Communication systems are subject to adversarial attacks since malevolent adversaries might harm and disrupt legitimate transmissions intentionally. Of particular interest in this paper are so-called denial-of-service (DoS) attacks in which the jammer completely prevents any transmission. Arbitrarily varying classical-quantum channels, providing a suitable model to capture the jamming attacks of interest, are studied. Algorithmic detection frameworks are developed based on Turing machines and also Blum-Shub-Smale (BSS) machines, where the latter can process and store arbitrary real numbers. It is shown that Turing machines are not capable of detecting DoS attacks. However, BSS machines are capable thereof implying that real number signal processing enables the algorithmic detection of DoS attacks.
In the practical Continuous Variable Quantum Key Distribution (CVQKD) system, there is a large gap between the ideal theoretical model and the actual physical system. There are still some inevitable flaws, which give quantum hackers the opportunity to manipulate the channel in complex communication environments and launch Denial of Service attacks on the quantum channel. Therefore, a DoS attack-aware defense scheme for the CVQKD system based on convolutional neural networks (CNN) is proposed. The simulation results show that the proposed model can effectively detect DoS attacks launched by quantum hackers in CVQKD system in a complex communication environment, and the model has strong robustness due to the addition of the attention mechanism module. In addition, multiple sets of comparative experiments show that compared with the existing artificial neural network model, the CNN-based model has higher accuracy and stability.
This article proposes a novel algorithm, named quantum multiagent actor–critic networks (QMACN) for autonomously constructing a robust mobile access system employing multiple unmanned aerial vehicles (UAVs). In the context of facilitating collaboration among multiple UAVs, the application of multiagent reinforcement learning (MARL) techniques is regarded as a promising approach. These methods enable UAVs to learn collectively, optimizing their actions within a shared environment, ultimately leading to more efficient cooperative behavior. Furthermore, the principles of quantum computing (QC) are employed in our study to enhance the training process and inference capabilities of the UAVs involved. By leveraging the unique computational advantages of QC, our approach aims to boost the overall effectiveness of the UAV system. However, employing a QC introduces scalability challenges due to the near intermediate-scale quantum (NISQ) limitation associated with qubit usage. The proposed algorithm addresses this issue by implementing a quantum centralized critic, effectively mitigating the constraints imposed by NISQ limitations. Additionally, the advantages of the QMACN with performance improvements in terms of training speed and wireless service quality are verified via various data-intensive evaluations. Furthermore, this article validates that a noise injection scheme can be used for handling environmental uncertainties in order to realize robust mobile access.