We study cyber security issues in networked control of a linear dynamical system. Specifically, the dynamical system and the controller are assumed to be connected through a communication channel ...that face malicious attacks as well as random packet losses due to unreliability of transmissions. We provide a probabilistic characterization for the link failures which allows us to study combined effects of malicious and random packet losses. We first investigate almost sure stabilization under an event-triggered control law, where we utilize Lyapunov-like functions to characterize the triggering times at which the plant and the controller attempt to exchange state and control data over the network. We then provide a look at the networked control problem from the attacker's perspective and explore malicious attacks that cause instability. Finally, we demonstrate the efficacy of our results with numerical examples.
With the proliferation of training data, distributed machine learning (DML) is becoming more competent for large-scale learning tasks. However, privacy concerns have to be given priority in DML, ...since training data may contain sensitive information of users. In this paper, we propose a privacy-preserving ADMM-based DML framework with two novel features: First, we remove the assumption commonly made in the literature that the users trust the server collecting their data. Second, the framework provides heterogeneous privacy for users depending on data's sensitive levels and servers' trust degrees. The challenging issue is to keep the accumulation of privacy losses over ADMM iterations minimal. In the proposed framework, a local randomization approach, which is differentially private, is adopted to provide users with self-controlled privacy guarantee for the most sensitive information. Further, the ADMM algorithm is perturbed through a combined noise-adding method, which simultaneously preserves privacy for users' less sensitive information and strengthens the privacy protection of the most sensitive information. We provide detailed analyses on the performance of the trained model according to its generalization error. Finally, we conduct extensive experiments using real-world datasets to validate the theoretical results and evaluate the classification performance of the proposed framework.
We consider the average consensus problem for the multi‐agent system in the discrete‐time domain. Three triggering based control protocols are developed, which dictate the broadcast and control ...update instants of individual agents to alleviate communication and computational burden. Lyapunov‐based design methods prescribe when agents should communicate and update their control so that the network converges to the average of agents' initial states. We start with a static version of the distributed event‐triggering law and then generalize it so that it involves an internal auxiliary variable to regulate the threshold dynamically for each agent. The third protocol uses a self‐triggering algorithm to avoid continuous listening wherein each agent estimates its next triggering time and broadcasts it to its neighbors at the current triggering time. Numerical simulations are shown to validate the efficacy of the proposed algorithms.
In this paper, we provide an overview of recent research efforts on networked control systems under denial-of-service attacks. Our goal is to discuss the utility of different attack modeling and ...analysis techniques proposed in the literature for addressing feedback control, state estimation, and multi-agent consensus problems in the face of jamming attacks in wireless channels and malicious packet drops in multi-hop networks. We discuss several modeling approaches that are employed for capturing the uncertainty in denial-of-service attack strategies. We give an outlook on deterministic constraint-based modeling ideas, game-theoretic and optimization-based techniques and probabilistic modeling approaches. A special emphasis is placed on tail-probability based failure models, which have been recently used for describing jamming attacks that affect signal to interference-plus-noise ratios of wireless channels as well as transmission failures on multi-hop networks due to packet-dropping attacks and non-malicious issues. We explain the use of attack models in the security analysis of networked systems. In addition to the modeling and analysis problems, a discussion is provided also on the recent developments concerning the design of attack-resilient control and communication protocols.
In this article, we study communication-constrained networked control problems for linear time-invariant systems in the presence of Denial-of-Service (DoS) attacks, namely attacks that prevent ...transmissions over the communication network. Our article aims at exploring the tradeoffs between system resilience and network bandwidth capacity. Given a class of DoS attacks, we characterize the bit-rate conditions that are dependent on the unstable eigenvalues of the dynamic matrix of the plant and the parameters of DoS attacks, under which exponential stability of the closed-loop system can be guaranteed. Our characterization clearly shows the tradeoffs between the communication bandwidth and resilience against DoS. An example is given to illustrate the proposed approach.
Multi-agent consensus under jamming attacks is investigated. Specifically, inter-agent communications over a network are assumed to fail at certain times due to jamming of transmissions by a ...malicious attacker. A new stochastic communication protocol is proposed to achieve finite-time practical consensus between agents. In this protocol, communication attempt times of agents are randomized and unknown by the attacker until after the agents make their communication attempts. Through a probabilistic analysis, we show that the proposed communication protocol, when combined with a stochastic ternary control law, allows agents to achieve consensus regardless of the frequency of attacks. We demonstrate the efficacy of our results by considering two different strategies of the jamming attacker: a deterministic attack strategy and a more malicious communication-aware attack strategy.
Summary
We consider an event‐triggered update scheme for the problem of multiagent consensus in the presence of faulty and malicious agents within the network. In particular, we focus on the case ...where the agents take integer (or quantized) values. To keep the regular agents from being affected by the behavior of faulty agents, algorithms of the mean subsequence reduced type are employed, where neighbors taking extreme values are ignored in the updates. Different from the real‐valued case, the quantized version requires the update rule to be randomized. We characterize the error bound on the achievable level of consensus among the agents as well as the necessary structure for the network in terms of the notion of robust graphs. We verify via a numerical example the effectiveness of the proposed algorithms.
In wireless sensor networks, a high level of accuracy is required in time synchronization to maintain time consistency of sensed data and to reduce idle listening times. In this technical note, we ...propose two fully distributed protocols for time synchronization. They are based on algorithms of multi-agent consensus and hence do not require any leader node. Further, they employ an event-based scheme to enhance communication efficiency. We analyze their convergence properties and show that clock synchronization can be achieved with less communication at guaranteed precision.
The paper assesses the cyber-security of power systems static state estimation (SE) in the possible presence of phasor measurement units (PMUs). Attacks are considered in the Jacobian matrix or the ...measurement function of the state estimation leading to the presence of coordinated leverage points. Leverage points, which are outliers, constitute a very challenging attack configuration even if randomly present. It is shown that coordinated cyber-attacks when applied to the Jacobian matrix raise major concerns about robust SE. The vulnerability of the least trimmed squares (LTS) estimator, which is robust towards leverage points, is shown. More generally, the weaknesses of robust regression equivariant estimators are discussed if attacks are developed and optimized based on a projection framework. Attack scenarios are outlined considering the number of attacked Jacobian elements, a decomposition of the system to maximize robustness, and whether a DC or AC formulation is used by the operator. Stealthy attacks that stay undetected with respect to the robust LTS are studied. Masked attacks are defined as well. Some possible solutions and remedial actions are proposed. Robust state estimation methods are evaluated and compared in the presence of different configurations of attacks through Monte Carlo simulations on the IEEE 14- and 30-bus test beds.
In the search engine of Google, the PageRank algorithm plays a crucial role in ranking the search results. The algorithm quantifies the importance of each web page based on the link structure of the ...web. We first provide an overview of the original problem setup. Then, we propose several distributed randomized schemes for the computation of the PageRank, where the pages can locally update their values by communicating to those connected by links. The main objective of the paper is to show that these schemes asymptotically converge in the mean-square sense to the true PageRank values. A detailed discussion on the close relations to the multi-agent consensus problems is also given.
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