Average consensus is extensively used in distributed networks for computation and control, where all the agents constantly communicate with each other update their states order to reach an agreement. Under a general average algorithm, information exchanged through wireless or wired communication could lead disclosure of sensitive private information. In this article, we propose privacy-preserving push-sum approach directed that can protect privacy while achieving simultaneously. Each node...

In this paper, we consider remote state estimation in an adversarial environment. A sensor forwards local estimates to a estimator over vulnerable network, which may be congested by intelligent denial-of-service attacker. It is assumed that the acknowledgment information from hidden attacker, which, thus, leads asymmetric between and Considering infinite-time goals of two agents their structure, model conflicting nature attacker stochastic Bayesian game. Solutions for game under different...

We consider remote state estimation in the presence of an active eavesdropper. A sensor forward local estimates to a estimator over network, which may be eavesdropped by intelligent adversary. Aiming at improving eavesdropping performance efficiently, adversary adaptively alternate between and mode. In contrast eavesdropping, attack enables sabotage data transfer estimator, improve reception itself same time. However, launching attacks increase risk being detected. As result, tradeoff...

This article considers the sensor scheduling for multiple dynamic processes. We consider n linear The state of each process is measured by a sensor, which transmits its local estimate over one wireless channel to remote estimator with certain communication costs. At time step, only portion sensors are allowed transmit data and packet might be lost due unreliability channels. Our goal find policy that coordinates in centralized manner minimize total expected estimation error formulate problem...

Unsupervised domain adaptation (UDA) frameworks have shown good generalization capabilities for 3D point cloud semantic segmentation models on clean data. However, existing works overlook adversarial robustness when the source itself is compromised. To comprehensively explore of UDA frameworks, we first design a stealthy generation attack that can significantly contaminate datasets with only minor perturbations to surface. Based that, propose novel dataset, AdvSynLiDAR, comprising...

This letter studies remote state estimation under denial-of-service (DoS) attacks. A sensor transmits its local estimate of an underlying physical process to a estimator via wireless communication channel. DoS attacker is capable interfere the channel and degrades accuracy. Considering tactical jamming strategies played by attacker, adjusts transmission power. interactive between studied in framework zero-sum stochastic game. To derive their optimal power schemes, we first discuss existence...

We study the denial-of-service (DoS) attack power allocation optimization in a multiprocess cyber-physical system (CPS), where sensors observe different dynamic processes and send local estimated states to remote estimator through wireless channels, while DoS attacker allocates its on channels as interference reduce transmission rates, thus degrading estimation accuracy of estimator. consider two problems. One is maximize average error processes, other minimal one. formulate these problems...

This paper addresses security issues of a cyber-physical system (CPS) under denial-of-service (DoS) attacks. The measurements sensor are transmitted to remote estimator over vulnerable communication channel, which may be congested by an intelligent attacker. Aiming at improving the estimation accuracy limited energy budget, we propose novel acknowledgement-based (ACK-based) cheating scheme for confuse attacker, from prove optimal deception-based transmission schedule within whole...

The past few years have witnessed the explosive growth of Internet Things (IoT) devices. necessity real-time edge intelligence for IoT applications demands that decision making must take place right here now at network edge, thus dictating a high percentage created data should be stored and analyzed locally. However, computing resources are constrained amount local is often very limited nodes. To tackle these challenges, we propose distributionally robust optimization (DRO)-based framework,...

This paper considers the remote state estimation in a cyber-physical system (CPS) using multiple sensors. The measurements of each sensor are transmitted to estimator over shared channel, where simultaneous transmissions from other sensors regarded as interference signals. In such competitive environment, needs choose its transmission power for sending data packets taking into account sensors' behavior. To model this interactive decision-making process among sensors, we introduce...

In this work, we consider the multi-party privacy conflict (MPC) in an online social network (OSN). As many data items uploaded to OSN are "co-owned" by multiple users with different concerns, some personal information of may be disclosed others unintentionally. On contrary existing mainstream platforms allowing only very user uploading set level, article take a fine-grained approach resolve MPC, which all co-owners independently determine whether share their content within on OSN....

This paper considers security issues of a cyber-physical system (CPS) under denial-of-service (DoS) attacks. The measurements multiple sensors are transmitted to remote estimator over multi-channel network, which may be congested by an intelligent attacker. Aiming at improving the estimation accuracy, we first propose novel aggregation scheme for produce accurate state estimates, from obtain closed-form expression expected error covariance. We further develop sensor-attacker game design...

Here we consider the problem of designing finite-impulse-response (FIR) graph filter (GF) in a fully distributed way. For directed with N nodes, each node designs coefficients manner, when knowledge structure, recognized as global information, is unavailable to node. By modeling signal shifting observations at linear dynamical system, establish fundamental connections between local response anode, concerned processing (GSP) field, and observability investigated control theory. The...

We consider a remote state estimation system under privacy-disclosure threats. A malicious agent eavesdrops the output of sensor node and infers some critical information about internal states which is measuring. Consequently, user privacy may be compromised. In order to avoid leakage, we propose novel data-driven power allocation scheme, enables us obtain closed-form expression expected error covariances. use covariances as metrics quantify accuracy privacy. By studying tradeoff between...

This paper explores distributed aggregative games in multi-agent systems. Current methods for finding Nash equilibrium require players to send original messages their neighbors, leading communication burden and privacy issues. To jointly address these issues, we propose an algorithm that uses stochastic compression save resources conceal information through random errors induced by compression. Our theoretical analysis shows the guarantees convergence accuracy, even with aggressive used...

In this paper, we develop distributed computation algorithms for Nash equilibriums of linear quadratic network games with proven differential privacy guarantees. a game each player's payoff being function, the dependencies decisions in function naturally encode structure governing players' inter-personal influences. Such social influence and individual marginal payoffs players indicate economic spillovers preferences, thus they are subject to concerns. For computing equilibrium,...

The distributed computation of a Nash equilibrium (NE) for non-cooperative games is gaining increased attention recently. Due to the nature systems, privacy and communication efficiency are two critical concerns. Traditional approaches often address these concerns in isolation. This work introduces unified framework, named CDP-NES, designed improve privacy-preserving NE seeking algorithm over directed graphs. Leveraging both general compression operators noise adding mechanism, CDP-NES...