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This article studies the attack detection problem of cyber–physical systems (CPSs) with the event-triggered (ET) mechanism. A switching-based moving-target defense (MTD) strategy is developed to detect malicious false-data-injection (FDI) attacks, which is characterized by the average dwell-time (ADT) property. Even if attacks may remain stealthy when the MTD mechanism is adopted, the impact of these stealthy attacks on the system performance is relatively small when the switching signal is unknown to the adversary. In order to reduce the cost of data transmission, an ET mechanism is added into the system. Furthermore, we prove that there exists a lower bound of the execution interval, which indicates that the Zeno phenomenon is excluded. Finally, numerical examples are employed to illustrate the effectiveness of the main results. [ABSTRACT FROM AUTHOR]

This article proposes a novel attack detection approach based on zonotopes for linear parameter-varying (LPV) systems with unknown-but-bounded (UBB) noises. The following three types of attacks are considered: 1) denial-of-service (DoS) attacks; 2) replay attacks (RAs); and 3) false-data-injection (FDI) attacks. In order to reduce the conservativeness, a free-weighting matrix is introduced, which can be computed by solving an optimization problem. Moreover, the radius of the intersection zonotope can be guaranteed to be limited as well. Furthermore, it is not necessary to acquire the knowledge about the specific type of attack in advance. Finally, a numerical example is given to illustrate the validity of the given method. [ABSTRACT FROM AUTHOR]

In this paper, we consider remote state estimation with simultaneous wireless information and power transfer (SWIPT). A remote estimator receives the state estimate transmitted by a sensor and sends an acknowledgment (ACK) signal to the sensor via a feedback wireless channel. The sensor has no other energy supply except that it can harvest wireless energy from the received ACK signal, which carries information and energy simultaneously. Since the symbol error rate of the state estimate transmitted by the sensor depends on the sensor’s transmission power allocation, there exists a tradeoff between the accuracy of the state estimate received by the remote estimator and the transmission power consumption of the sensor. Moreover, the sensor’s transmission power is restricted by the remaining energy level in its battery, which is decided by the amount of the harvested wireless energy. Therefore, we jointly optimize the transmission power allocation of the remote estimator and the sensor and formulate the optimization problem into an infinite time-horizon average cost Markov decision process (MDP). We first prove the existence of the optimal stationary power allocation policy, and then present the monotonic structures of the optimal policy. Simulation results are provided to verify and illustrate the main results. [ABSTRACT FROM AUTHOR]

This article studies a security issue in remote distributed consensus estimation where sensors transmit their measurements to remote estimators via a wireless communication network. The relative entropy is utilized as a stealthiness metric to detect whether the data transmitted through the wireless network are attacked. The performance degradation induced by an attacker that attempts to be stealthy or undetected is analyzed, and the corresponding false-data attack strategy is characterized, which can achieve the maximal integrated mean-square error (IMSE). Finally, the tradeoff between the performance degradation and attack stealthiness level is evaluated through an example. [ABSTRACT FROM AUTHOR]

In this article, a data-driven design scheme of undetectable false data-injection attacks against cyber-physical systems is proposed first, with the aid of the subspace identification technique. Then, the impacts of undetectable false data-injection attacks are evaluated by solving a constrained optimization problem, with the constraints of undetectability and energy limitation considered. Moreover, the detection of designed data-driven false data-injection attacks is investigated via the coding theory. Finally, the simulations on the model of a flight vehicle are illustrated to verify the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

This brief investigates the problem of denial-of-service (DoS) attacks against linear quadratic regulator (LQR) control channels. Owing to energy constraints, the attacker can only launch consecutive DoS attacks with a certain length $m$ to block communication channels between the controller and actuator. We consider two compensation strategies commonly found in the literature, namely, zero-input and hold-input when control packets are blocked. It is shown that jamming from the initial instant is not always optimal for attackers. Necessary and sufficient conditions are given to ensure the optimality of blocking from the initial instant despite the randomness of initial states. In the case where attackers know the initial state, a finite-interval search method is given to obtain the optimal starting instant of DoS attacks. Numerical examples illustrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

In this brief, the data-driven design of sparse undetectable sensor attacks against cyber-physical systems is studied, with the aid of subspace approach. First, the undetectable and sparse sensor attack design schemes are proposed based on the physical models. Then the data-driven realizations of sparse undetectable sensor attacks are designed via identifying the subspace from the collected input and output data. Moreover, the impacts of sparse undetectable sensor attacks are evaluated by solving the constraint optimization problems. Finally, the simulations on an unmanned aerial vehicle are illustrated to testify the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

In this brief, a proposed topology for a wireless networked control system is studied under several cyber attack scenarios, and a distributed intrusion detection system (IDS) is designed to identify the existence of attacks. More specifically, this brief presents a modelling framework for the closed-loop control system with the IDS and a computational procedure to design and compute the IDS. The computational procedure delivers a stable closed-loop control system with the IDS being sensitive to cyber attacks. Also, a simulation example is used to illustrate the application of the proposed procedure as well as its effectiveness. [ABSTRACT FROM AUTHOR]

Multi-component based Log-Structured Merge-tree (LSM-tree) has been becoming one of the mainstream indexes. LSM-tree adopts component-by-component KV item flowing down mechanism to push each KV item from one smaller component to the adjacent larger component during compaction procedures until the KV items reach the largest component. This process incurs significant write amplification and limits the write throughput. In this paper, we propose one multi-component Skip-tree to aggressively push the KV items to the non-adjacent larger components via skipping some components and then make the KV items’ top-down move more efficient. We develop adaptive and reliable KV item movements among components. By reducing the number of steps during the flowing process from memory-resident component to the disk-resident largest component, Skip-tree can effectively reduce the write amplification and thus improve the system throughput. We design and implement one high performance key-value store, named SkipStore, based on Skip-tree. The experiments demonstrate that SkipStore outperforms the state-of-the-art open-sourced system RocksDB in Facebook by 66.5 percent under HDD and 61 percent under SSD. [ABSTRACT FROM PUBLISHER]