This paper investigates the event-triggered consensus problem of linear multi-agent systems (MASs) under distributed denial-of-service (DDoS) attacks from multiple attackers that target different communication channels. The joint connectivity of the physical topology induced by the DDoS attacks is analyzed, which is shown to be a necessary yet insufficient condition for the joint connectivity of the communication topology induced by the interaction between DDoS attacks and event-triggered communication. To ensure the joint connectivity of the resulting communication topology, the authors design a dynamic secure controller with a novel consensus protocol and a novel event-triggered mechanism that includes a communication recovery detection strategy. Then, asymptotic consensus is theoretically established, with a guaranteed exclusion of Zeno behavior. Finally, the effectiveness of the proposed approach is verified through numerical simulations.
With the rapid deployment of Cyber-Physical Systems in industrial and infrastructure sectors, ensuring their security has become a pressing challenge. In this paper, the challenge caused by data tamp ering is examined within the system identification framework using binary observations. An identification algorithm is first developed for the attack-free scenario, and the consistency of the estimated parameters is established. The convergence of parameter estimation under data tampering attacks is then analyzed, followed by the formulation of an optimal attack model with constraints, where absolute error is adopted as the performance metric. From the attacker’s perspective, the problem of achieving maximal attack impact with minimal energy is investigated, and both analytical and numerical solutions for optimal attack strategies under varying conditions are derived. Extensive simulation results validate the effectiveness of the proposed strategies.
In markets subject to institutional or compliance constraints, optimal execution under monotone constraints, which requires that the inventory trajectory must remain continuously monotone over the trading horizon, constitutes an important problem, directly affecting trading efficiency and market stability. A representative example arises from China’s T+1 trading rule, which prohibits investors from selling stocks purchased on the same day. Under a signature-based framework, enforcing such time-continuous monotonicity leads to a nontrivial structural difficulty: Pathwise feasibility must hold for all times, which induces a stochastic semi-infinite constraint. To address this difficulty, the authors propose a two-step approach: First, the authors robustify the pathwise stochastic constraints over time, yielding a deterministic semi-infinite program. Second, by exploiting the temporal structure of the uncertainty sets and the prefix structure of signatures, the authors derive an exact finite-dimensional reformulation of the resulting deterministic semi-infinite problem. The authors establish the consistency of the solution in the proposed framework, obtained from sample-based approximation of both the objective function and the feasible set, thus providing theoretical performance guarantees. Experiments on real market data show that the proposed framework strictly maintains pathwise monotone feasibility while achieving improved execution performance relative to standard benchmarks.
Attack defense and privacy protection are critical for secure consensus control of multi-agent systems (MASs). While prior studies have addressed these threats individually or jointly, this paper proposes a novel encoding-decoding-based consensus control strategy for discrete-time MASs under denial-of-service (DoS) attacks, leveraging a buffer-based switching mechanism and dynamic quantization to ensure both information availability and confidentiality. Based on the uniform quantizer, the authors first perform an encoding-decoding-based algorithm with a dynamic quantization factor. Thus, the information to be transferred to neighbors is encoded by the encoder and the received data from neighbors is decoded by the decoder, which can prevent information from being directly exposed. Furthermore, the problem of information interruption caused by DoS attacks can be solved by introducing a buffer that can save the latest state information when DoS attacks occur. A distributed controller with a switching mechanism is proposed by employing the stored and decoded state information. The linear matrix inequality (LMI) and the Lyapunov function are also used to get the switched control gains and sufficient conditions of the system’s stability. Finally, a numerical simulation example is provided to demonstrate the effectiveness of the developed control strategy.
