This article investigates a neural network (NN)‐based control problem for unknown discrete‐time nonlinear systems with a denial‐of‐service (DoS) attack and an adaptive event‐triggered mechanism ...(ETM). The considered DoS attacks are described by the occurrence frequency and durations and hence more general in comparison with existing stochastic models. To the addressed problem, a novel adaptive rule adjusting the triggering threshold of ETM is constructed to govern the communication schedule, and an NN‐based observer is designed to identify the system dynamics where a piecewise update rule of NN weights is adopted to handle the challenge of the complex time series coming from both ETM and DoS attacks. In light of this kind of protocol‐ and attack‐induced switched systems, a sufficient condition dependent on the occurrence frequency and durations of DoS attacks is elaborately established via the analysis of input‐to‐state stability. Furthermore, an iteration adaptive dynamic programming approach is proposed to handle the addressed control issue, and the boundedness is discussed to both the estimation errors of the Luenberger‐type observer and the identified errors of NN weights of observer networks as well as actor‐critic networks with the help of the Lyapunov theory. Finally, a simulation example is utilized to illustrate the usefulness of the proposed controller design scheme.
Detection and prevention of global navigation satellite system (GNSS) "spoofing" attacks, or the broadcast of false global navigation satellite system services, has recently attracted much research ...interest. This survey aims to fill three gaps in the literature: first, to assess in detail the exact nature of threat scenarios posed by spoofing against the most commonly cited targets; second, to investigate the many practical impediments, often underplayed, to carrying out GNSS spoofing attacks in the field; and third, to survey and assess the effectiveness of a wide range of proposed defences against GNSS spoofing. Our conclusion lists promising areas of future research.
This paper applies an input-based triggering approach to investigate the secure consensus problem in multiagent systems under denial-of-service (DoS) attacks. The DoS attacks are based on the ...time-sequence fashion and occur aperiodically in an unknown attack strategy, which can usually damage the control channels executed by an intelligent adversary. A novel event-triggered control scheme on the basis of the relative interagent state is developed under the DoS attacks, by designing a link-based estimator to estimate the relative interagent state between intermitted communication instead of the absolute state. Compared with most of the existing work on the design of the triggering condition related to the state measurement error, the proposed triggering condition is designed based on the control input signal from the view of privacy protection, which can avoid continuous sampling for every agent. Besides, the attack frequency and attack duration of DoS attacks are analyzed and the secure consensus is reachable provided that the attack frequency and attack duration satisfy some certain conditions under the proposed control algorithm. "Zeno phenomenon" does not exhibit by proving that there exist different positive lower bounds corresponding to different link-based triggering conditions. Finally, the effectiveness of the proposed algorithm is verified by a numerical example.
This brief presents the design of a distributed estimator for joint state and unknown input estimation of nonlinear systems subject to denial-of-service (DoS) attacks and stochastic disturbances. In ...contrast to the existing algorithms for distributed state estimation, the proposed estimation framework can also identify the unknown input. Moreover, non-periodic DoS attacks are considered that can independently compromise different communication links. To ensure resource conservation, an improved dynamic event-triggered (ET) mechanism is included in the proposed estimator. The new ET condition effectively reduces the unnecessary transmissions during DoS attacks as compared to the existing studies. Convergence of the estimator is established and the design conditions are presented as matrix inequalities. A simulation example is then used to verify the results.
To reduce the computational burden and resist the denial-of-service (DoS) attacks, a resilient distributed sampled-data control scheme is proposed for multiagent systems. The agent states are sampled ...periodically by the sensors. DoS attacks disrupt the data communication from transmitters to controllers randomly or periodically with a limited duration time. Information on DoS attacks can be obtained by introducing novel logic processors embedded in corresponding controllers. Next, the problem of resilient control can be converted into one concerned with the upper and lower bound of the sampling interval of an aperiodic sampled-data control system. Some sufficient criteria for developing resilient distributed controllers are derived using the novel looped Lyapunov functional approach and the free-matrix-based inequality method. Finally, two illustrative examples, unmanned aerial vehicles and the two-mass-spring systems, are provided to demonstrate the efficiency of the proposed resilient distributed sampled-data control protocols against the DoS attacks.
Internet of Things (IoT) and its applications are the most popular research areas at present. The characteristics of IoT on one side make it easily applicable to real-life applications, whereas on ...the other side expose it to cyber threats. Denial of Service (DoS) is one of the most catastrophic attacks against IoT. In this paper, we investigate the prospects of using machine learning classification algorithms for securing IoT against DoS attacks. A comprehensive study is carried on the classifiers which can advance the development of anomaly-based intrusion detection systems (IDSs). Performance assessment of classifiers is done in terms of prominent metrics and validation methods. Popular datasets CIDDS-001, UNSW-NB15, and NSL-KDD are used for benchmarking classifiers. Friedman and Nemenyi tests are employed to analyze the significant differences among classifiers statistically. In addition, Raspberry Pi is used to evaluate the response time of classifiers on IoT specific hardware. We also discuss a methodology for selecting the best classifier as per application requirements. The main goals of this study are to motivate IoT security researchers for developing IDSs using ensemble learning, and suggesting appropriate methods for statistical assessment of classifier’s performance.
Due to malicious cyber attacks, the frequency regulation of an islanded microgrid (MG) with load changes and wind/solar power fluctuations may not be guaranteed and the overall system may even be ...destabilized. The MG frequency control thus faces new challenges. In response to these challenges, this paper addresses a resilient load frequency control (LFC) problem for islanded AC-MGs under simultaneous false data injection (FDI) attacks and denial-of-service (DoS) attacks. Toward this aim, a new piecewise observer is constructed to provide the real-time estimates of the unavailable system state and the unknown FDI attack signal. Furthermore, a resilient <inline-formula> <tex-math notation="LaTeX">\mathcal {H}_{\infty } </tex-math></inline-formula> LFC scheme is developed to suppress the attack impacts. The novelty of this study lies in the development of an attack-parameter-dependent time-varying Lyapunov function approach to achieve stability analysis and resilient observer/controller design against concurrent FDI attacks and intermittent DoS attacks. Specifically, a tractable observer design criterion is first derived such that the estimation error is exponentially stable under a specified <inline-formula> <tex-math notation="LaTeX">\mathcal {H}_{\infty } </tex-math></inline-formula> performance level. Then a design criterion on the existence of the resilient controller is presented to guarantee the exponential stability of the resulting closed-loop system in the presence of the attacks, while preserving the anticipated <inline-formula> <tex-math notation="LaTeX">\mathcal {H}_{\infty } </tex-math></inline-formula> performance level. Finally, comparative simulation studies in various attack scenarios and different parameter settings are presented to verify the efficiency of the obtained theoretical results.
This paper develops a fully distributed framework to investigate the cooperative behavior of multiagent systems in the presence of distributed denial-of-service (DoS) attacks launched by multiple ...adversaries. In such an insecure network environment, two kinds of communication schemes, that is, sample-data and event-triggered communication schemes, are discussed. Then, a fully distributed control protocol with strong robustness and high scalability is well designed. This protocol guarantees asymptotic consensus against distributed DoS attacks. In this paper, "fully" emphasizes that the eigenvalue information of the Laplacian matrix is not required in the design of both the control protocol and event conditions. For the event-triggered case, two effective dynamical event-triggered schemes are proposed, which are independent of any global information. Such event-triggered schemes do not exhibit Zeno behavior even in the insecure environment. Finally, a simulation example is provided to verify the effectiveness of theoretical analysis.
This article presents a resilient model predictive control (MPC) framework to attenuate adverse effects of denial-of-service (DoS) attacks for cyber-physical systems (CPSs), where the system dynamics ...is modeled by a linear time-invariant system. A DoS attacker targets at blocking the controller to actuator (C-A) communication channel by launching adversarial jamming signals. We show that, in order to guarantee exponential stability of the closed-loop system, several conditions for resilient MPC should be satisfied. And these established conditions are explicitly related to the duration of DoS attacks and MPC parameters such as the prediction horizon and the terminal constraint. Two key techniques, including the μ-step positively invariant set and the modified initial feasible set are exploited for achieving exponential stability in the presence of DoS attacks. Moreover, the maximum allowable duration of the DoS attacker is also obtained by using the μ-step positively invariant set. Finally, the effectiveness of the proposed MPC algorithm is verified by simulated studies and comparisons.
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