Deception Attacks Research Articles

Secure State Estimation of Singularly Perturbed Switched Systems With Output Deception Attack via Discretized LKF Approach

Secure State Estimation of Singularly Perturbed Switched Systems With Output Deception Attack via Discretized LKF Approach

Integrated fault detection filter and fault-tolerant control for the unmanned surface vehicle with deception attacks

This article investigates the fault detection and fault-tolerant control problem for an unmanned surface vehicle exposed to wave-induced disturbances and actuator faults in the physical layer, and delays and deception attacks in the cyber layer. First, a comprehensive vehicle model that includes physical disturbances, faults, time-varying delays, and Bernoulli random variable–based deception attacks is established. Second, an integrated fault detection filter and fault-tolerant controller design are developed to simultaneously provide a high degree of sensitivity to actuator faults and robustness and stability against cyber-physical threats (disturbances, faults, delays, and attacks). Delays and deception attacks are assumed to occur on the channel from fault detection filter to fault-tolerant controller. Finally, the performance and advantages of the integrated fault detection filter and fault-tolerant controller method with the solvability of inequality matrices are evaluated via comparative simulations in the unmanned surface vehicle with both low and high forward speeds.

Adaptive robust control of nonaffine nonlinear systems via an improved event‐triggered mechanism

AbstractThis paper aims to address the problem of event‐based adaptive robust control for a class of nonaffine nonlinear systems against actuator faults and unknown deception attacks. Firstly, different from the widely used relative threshold triggering mechanism, an improved event‐triggered mechanism with the time‐varying function threshold is devised for effectively saving more communication costs between controller and actuator. Then, based on a class of modified filter‐based coordinate transformations and the improved event‐triggered mechanism, the intermediate virtual control laws are devised to construct actual controllers, which not only guarantees robust stabilization of the system but also relaxes the universal assumptions on control coefficients and attack weights. Besides, the design challenges resulting from the presence of coupling terms in the nonaffine nonlinear system are successfully overcome by virtue of mean value theorem and the property of fuzzy basis function. Theoretical analysis proves that all signals of the closed‐loop system are semiglobally uniformly ultimately bounded (SUUB) and the Zeno behavior can be averted. Finally, the effectiveness of the proposed strategy is verified via comprehensive simulation results.

Tracking control design for cyber‐physical systems with disturbances and input delays: An interval type‐2 fuzzy approach

SummaryThe underlying intention of this work is to devise a tracking control protocol for the nonlinear cyber‐physical systems that are prone to external disturbances, time‐varying input delays and deception attacks. To be more precise, the modified repetitive tracking controller is formulated for ensuring the asymptotic tracking outcomes of the assayed system with the aim of addressing the impacts caused by external disturbances as well as input time‐varying delays. First of all, the nonlinearities of the investigated cyber‐physical systems are efficaciously approximated by the interval type‐2 fuzzy model approach. Further, the predictor technique is utilized in this study to mitigate the influence of input delays and specifically, the extended Smith predictor approach is employed. That is, the transfer function is inserted into the conventional Smith predictor's main feedback channel. In parallel, the active disturbance rejection technique is executed to reject and estimate the external disturbance impacts on the assayed system. Notably, the improved equivalent‐input‐disturbance estimator approach is tied up and more precisely, the estimated disturbances obtained from the afore‐said estimator are incorporated into the proposed controller. Whilst the deception attacks are characterized as a stochastic distributed random variable that are governed by the Bernoulli distribution. With all of this as a backdrop, the appropriate delay‐dependent constraints are expressed in the context of linear matrix inequalities by employing the Lyapunov stability theory. In line with the predetermined criteria, the relations for computing the required gain matrices are also formulated. Ultimately, the simulation analysis is carried out using two distinct numerical examples to confirm the importance of the proposed control mechanism from the perspective of theory as well as practice.

Distributed finite‐time adaptive fault‐tolerant consensus control of second‐order multi‐agent systems under deception attacks

SummaryThis study addresses the issue of distributed fault‐tolerant consensus control for second‐order multi‐agent systems subject to simultaneous actuator bias faults in the physical layer and deception attacks in the cyber layer. Cyber‐physical threats (malicious state‐coupled nonlinear attacks and physical deflection faults), unknown control gains, external disturbances and uncertainties force the failure of the existing graph theory‐based consensus control schemes, leading to disruptions in the cooperation and coordination of multi‐agent systems. Then, the power integrator‐based virtual control is incorporated in the distributed fault‐tolerant consensus to achieve unknown parameter estimations with the adaptive technique. The consensus‐based robustness to lumped uncertainties, resilience to attacks, compensation to faults, and novel finite‐time convergence of the neighborhood errors and velocity errors are also realized within a prescribed finite‐time settling bound. The simulation is conducted to verify the effectiveness of the distributed finite‐time adaptive fault‐tolerant consensus algorithm.

Quickest detection of bias injection attacks on the glucose sensor in the artificial pancreas under meal disturbances

Modern glucose sensors deployed in closed-loop insulin delivery systems, so-called artificial pancreas use wireless communication channels. While this allows a flexible system design, it also introduces vulnerability to cyberattacks. Timely detection and mitigation of attacks are imperative for device safety. However, large unknown meal disturbances are a crucial challenge in determining whether the sensor has been compromised or the sensor glucose trajectories are normal. We address this issue from a control-theoretic security perspective. In particular, a time-varying Kalman filter is employed to handle the sporadic meal intakes. The filter prediction error is then statistically evaluated to detect anomalies if present. We compare two state-of-the-art online anomaly detection algorithms, namely the χ2 and CUSUM tests. We establish a robust optimal detection rule for unknown bias injections. Even if the optimality holds only for the restrictive case of constant bias injections, we show that the proposed model-based anomaly detection scheme is also effective for generic non-stealthy sensor deception attacks through numerical simulations.

Security sliding mode control for T-S fuzzy systems under attack probability-dependent dynamic round-robin protocol

In this paper, the security control problem for T-S fuzzy systems is investigated through the sliding mode control (SMC) strategy. Consider deception attacks occurring randomly, a multi-modes round-robin protocol is proposed on the sensor-to-controller channel. Under this protocol, the number of transmitted nodes can be dynamically adjusted according to attack probability and system state so as to balance the relationship between system performance and communication transmission. The fuzzy sliding mode controller depending on the scheduling signal is constructed, whose membership functions (MFs) are different from the ones of the controlled system. In addition, by using the membership-function-dependent (MFD) stability analysis method, appropriate sufficient conditions are derived to ensure both the stochastic stability and the reachability. Finally, simulation results are presented to prove the proposed SMC strategy.

Sampled-data stabilization for networked control systems under deception attack and the transmission delay

For the stability analysis and stabilization synthesis problems, this paper considers networked control systems (NCSs) with the transmission delay and the deception attack under aperiodic samplings, where the deception attack and its activation function are represented as a sector bound function and a random variable with Bernoulli distribution, respectively. This paper proposes the stability and stabilization criteria for the NCSs by constructing Lyapunov–Krasovskii (L–K) functionals with continuous functionals and looped-functionals. Compared with the literature, the proposed continuous functionals take into account the mixed delay including the transmission delay and the maximum allowable sampling interval, as well as the augmented vector and integral terms. Also, the proposed looped-functionals construct two augmented vectors with integral vectors that are zeros at t=tk and t=tk+1, respectively. By utilizing these two augmented vectors, the looped-functionals fully utilize the sampling patterns compared with the literature. Based on the proposed L–K functionals, this paper derives not only the stability criterion for the NCSs with the transmission delay, but also the stabilization criterion for the NCSs with the transmission delay and the deception attack in terms of linear matrix inequalities (LMIs), respectively. Numerical example demonstrates the validity of the proposed approach.

An adaptive dynamic programming method for observer‐based sliding mode control of connected vehicles subject to deception attacks

AbstractThis article investigates the problem of optimal observer‐based sliding mode control (SMC) of connected vehicles subject to deception attacks and disturbances with adaptive dynamic programming (ADP) method. For a group of vehicles with unknown nonlinear dynamics term and disturbance, this article aims to give a control methodology to achieve secure tracking of the desired spacing, velocity and acceleration. A neural network (NN) and an observer are constructed to estimate the unknown nonlinear term and the states, respectively. Then, a SMC scheme incorporating NN approximation is developed and an off‐policy ADP method is used to implement the optimal control of sliding mode dynamics. The proposed method can ensure individual stability and string stability of the set of vehicles. Numerical simulations are conducted to demonstrate the validity of the proposed controller.

Adaptive neural control for delayed discrete-time switched systems under deception attacks

This paper focuses on the issue of adaptive neural control for discrete-time switched systems with time delay and deception attacks. Firstly, the switching signal is constrained by the dwell time. Considering that the deception attacks are unknown, the neural network technique is employed to approximate the attack signals. Then, an adaptive state feedback controller is established to compensate for the adverse effects of deception attacks for switched systems. Meanwhile, sufficient conditions for the boundedness of the switched system are given through the Lyapunov functional method, and the controller gains can be obtained by resolving the linear matrix inequality. Finally, the feasibility of the proposed method is illustrated via a numerical example.

Prescribed Fixed-Time Control for Constrained Uncertain Nonlinear Cyber-Physical Systems Against Deception Attacks.

In this note, a novel prescribed fixed-time adaptive tracking control scheme is developed to cope with the fixed-time tracking control issue for a category of constrained MIMO nonlinear cyber-physical systems (CPSs) with exogenous perturbations, which suffer from deception attacks started in controller-actuator (C-A) channel. Distinguished from the conservative dynamic surface control (DSC) schemes with a linear filter, a novel nonlinear filter is designed in our strategy, which can tackle the intrinsic issue of explosion of computational complexity and promote the system performance. Besides, a new barrier Lyapunov function (BLF) is designed to ulteriorly enhance the tracking performance on the basis of the prescribed performance function (PPF) approach. Prominently, the proposed control strategy could accommodate the exogenous interferences and deception attacks simultaneously. Furthermore, we have substantiated that the developed approach can not only make certain that all the tracking errors of the resulting closed-loop system, including output tracking errors and virtual tracking errors, enter a prespecified small region near equilibrium point with fixed-time convergence rate, but also guarantee them obey the corresponding constraints throughout the entire control operation, where the regulation time and the tracking accuracy level keep prior known and could be prespecified arbitrarily. Finally, the validity and effectiveness of the proposed control scheme are illustrated through a representative application instance.

Adaptive Dynamic Surface Control for Uncertain Nonlinear Time-Delay Cyber-Physical Systems Under Injection and Deception Attacks

Adaptive Dynamic Surface Control for Uncertain Nonlinear Time-Delay Cyber-Physical Systems Under Injection and Deception Attacks

Resilient Adaptive Stabilization for Nonlinear CPSs Dealing With Deception Attacks

Resilient Adaptive Stabilization for Nonlinear CPSs Dealing With Deception Attacks

Finite-Time Nonfragile Synchronization Control of Time-Varying Delays T-S Fuzzy Discrete Chaotic Network Systems With Deception Attacks

Finite-Time Nonfragile Synchronization Control of Time-Varying Delays T-S Fuzzy Discrete Chaotic Network Systems With Deception Attacks

Disturbance Observer-Based H ∞ Control for Interval Type-2 Fuzzy Hidden Markov Jump Systems Subject to Deception Attacks.

This article presents a composite anti-disturbance security control approach for the continuous-time nonlinear hidden Markov jump systems, in which the nonlinearities are characterized by the interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy model. To offset and suppress the influence of multiple disturbances on the system stability, a composite control method based on disturbance observer and H∞ control is established. In addition, considering potential cyber-attacks, this article takes deception attacks as an example, assuming that the attack signal is generated by a nonlinear bounded function, and the Bernoulli distribution is employed to depict whether the attack occurs or not. Then, in accordance with the IT2 T-S fuzzy model, the final composite system is derived. With the help of tools, such as the Lyapunov stability theory and fuzzy theory, the stability of the target system is analysed, and the specific forms of the fuzzy composite controller and disturbance observer are obtained. Finally, the correctness and effectiveness of the control method proposed in this article are verified through two examples.

Data-driven Tracking Control of Nonlinear Systems under Deception Attacks and Packet Loss

Data-driven Tracking Control of Nonlinear Systems under Deception Attacks and Packet Loss

Kalman Filter of Switching System Under Hybrid Cyber Attack

Potential malicious attacks have been a significant security concern for network system applications. However, there are few studies on filtering for hybrid network attacks in switching systems. This paper considers a Kalman filtering problem for the switched systems that suffer from deception attacks and denial-of-service attacks. A new network transmission model for switching systems is established. Then, based on the minimum mean square error criterion, a Kalman filter with low conservatism is designed for the discrete-time switched system. The newly switched Kalman gain matrix is deduced including the random variation of the switching signal after being attacked by the network. Finally, the effectiveness of the proposed filter is verified by the numerical simulation. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —A switching system is considered to be a typical hybrid system. As it often works in a network environment, the switching signal is vulnerable to the network and thus to various cyber-attacks (e.g. spoofing attacks and denial-of-service attacks). Few studies have been conducted on the impact of switching signals in network transmission. To address this problem, this paper proposes a Kalman filter design method with low conservativeness, which describes network attacks and data loss by building a Kalman filter model associated with the switching signal in terms of satisfying Bernoulli random variables. For practitioners, the ability to recover data to a certain extent when the data transmission is affected by different network attacks will save a lot of costs and is important for improving the stability and performance of switching systems. Our future work will aim to improve the performance of different filtering algorithms under different cyber-attacks.

Distributed Secure Surrounding Control for Multiple USVs against Deception Attacks: A Stackelberg Game Approach with Reinforcement Learning

Distributed Secure Surrounding Control for Multiple USVs against Deception Attacks: A Stackelberg Game Approach with Reinforcement Learning

Adaptive Prescribed-Time Consensus Tracking Control Scheme of Nonlinear Multi-Agent Systems Under Deception Attacks

Adaptive Prescribed-Time Consensus Tracking Control Scheme of Nonlinear Multi-Agent Systems Under Deception Attacks

Distributed Model-Free Adaptive Predictive Control for MIMO Multi-Agent Systems With Deception Attack

Distributed Model-Free Adaptive Predictive Control for MIMO Multi-Agent Systems With Deception Attack