Stochastic Deception Attacks Research Articles

Quasi-Consensus Control for a Class of Time-Varying Stochastic Nonlinear Time-Delay Multiagent Systems Subject to Deception Attacks

This article focuses on the consensus control problem for a class of time-varying stochastic nonlinear time-delay multiagent systems (MASs) attacked by deception attacks. The stochastic deception attack is considered in the procedure of propagating measurement information among agents. To solve the consensus control problem for addressed MASs under stochastic deception attacks, a definition of quasi-consensus is put forward. The objective of our investigation is to devise a consensus protocol to drive all agents to stay within an allowable range despite the existence of stochasticity and external malicious attacks. With the help of recursive linear matrix inequality and stochastic analysis methods, sufficient conditions are acquired to guarantee that all agents are constrained in the desirable range. Subsequently, an optimization algorithm is presented, which is to seek the locally optimal allowable distance among agents. Finally, a simulation example is presented to demonstrate the availability of our proposed algorithm.

Exponential synchronization of coupled neural networks under stochastic deception attacks

In this paper, the issue of synchronization is investigated for coupled neural networks subject to stochastic deception attacks. Firstly, a general differential inequality with delayed impulses is given. Then, the established differential inequality is further extended to the case of delayed stochastic impulses, in which both the impulsive instants and impulsive intensity are stochastic. Secondly, by modeling the stochastic discrete-time deception attacks as stochastic impulses, synchronization criteria of the coupled neural networks under the corresponding attacks are given. Finally, two numerical examples are provided to demonstrate the correctness of the theoretical results.

An event‐triggered approach to security control for networked systems using hybrid attack model

AbstractThis article presents an event‐triggered approach to security control for networked systems by using hybrid attack model. Stochastic deception attacks, replay attacks, and denial of service attacks are assumed to occur in the communication network. The main contribution of the article is that an event‐triggered control strategy is presented to stabilize the networked systems based on the hybrid attacks and the network resource limitations. A novel event‐based model for networked control systems under hybrid attacks is established. Based on the proposed model, sufficient conditions are acquired to guarantee the closed‐loop system stability and the controller design method is developed. Finally, two simulation examples are given to validate the feasibility of the proposed method.

Dynamic event-triggered [formula omitted] control for networked control systems under deception attacks: a switching method

Based on the event-triggered scheme (ETS), the L∞ control problem is considered for networked control systems subject to stochastic deception attacks. A novel dynamic switching ETS is proposed to reduce the number of transmitted signals. A stochastic model is used for deception attacks, where the system states are corrupted by attackers. Under this framework, the system to be investigated is modeled as a new switched system. By using the constructed Lyapunov function, sufficient criteria are derived to guarantee the exponential mean-square stability and L∞ performance. Subsequently, the corresponding controller is designed. Finally, the effectiveness of the dynamic ETS is illustrated by using an unmanned aerial vehicle system.

Event-based asynchronous and resilient filtering for Markov jump singularly perturbed systems against deception attacks

The dynamic event-based asynchronous and resilient dissipative filter design for Markov jump singularly perturbed systems (MJSPSs) against stochastic deception attacks is discussed in this paper. Firstly, a novel dynamic event-based transmission protocol is provided to further decrease the proportion of sampled data into network. The effect of deception attacks is formulated as a random variable satisfying the Bernoulli distribution. And an asynchronous filter is delicately constructed. Based on the technique of linear matrix inequality (LMI), efficient criteria of stochastically stable for the filtering error systems with a predetermined dissipative performance are obtained. An effective method of jointly design the proposed dynamic event-triggered transmission protocol and the non-synchronous filter is offered. Lastly, a numerical instance and a resistance-capacitance (RC) circuit system are provided to display the effectiveness and the benefit of the developed method.

Event-Triggered Output Feedback Synchronization of Master-Slave Neural Networks Under Deception Attacks.

The problem of event-triggered synchronization of master-slave neural networks is investigated in this article. It is assumed that both communication channels from the sensor to controller and from controller to actuator are subject to stochastic deception attacks modeled by two independent Markov processes. Two discrete event-triggered mechanisms are introduced for both channels to reduce the number of data transmission through the communication channels. To comply with practical point of view, static output feedback is utilized. By employing the Lyapunov-Krasovskii functional method, some sufficient conditions on the synchronization of master-slave neural networks are derived in terms of linear matrix inequalities, which make it easy to design suitable output feedback controllers. Finally, a numerical example is presented to show the effectiveness of the proposed method.

Security control of interval type-2 fuzzy system with two-terminal deception attacks under premise mismatch

This paper focuses on security control of nonlinear networked control systems with parameter uncertainties. Interval type-2 T–S fuzzy model is used to represent the original nonlinear system, so as to capture the parameter uncertainties. Stochastic deception attacks are considered in the sensor to controller channel and the controller to actuator channel. By constructing Lyapunov–Krasovskii functional with the information of time-varying delays in the deception attacks, new stabilization conditions are derived. Furthermore, considering the information of upper and lower bounds of membership functions, less conservative membership-function-dependent conditions are developed in terms of linear matrix inequality. Finally, simulation results show that the proposed method is effective under the influence of deception attacks and parameter uncertainties.

Event-triggered distributed fault detection and control of multi-weighted and multi-delayed large-scale systems

This paper addresses the problem of distributed simultaneous fault detection and control (SFDC) of multi-weighted and multi-delayed (MWMD) large-scale interconnected systems which are subjected to event-triggered communication, nonlinear perturbations, measured output quantization, redundant channels, and stochastic deception attacks. The large-scale systems under consideration have multiple coupling links between neighboring subsystems, and all the links are considered to have different coupling weights and delays. A distributed fault detector and controller (FDC) module is designed to guarantee the exponential mean square stability of the overall closed-loop system along with a prescribed extended dissipative control performance and H∞ fault detection performance. The gain parameters of the distributed fault detector and controller module are determined by using the cone complementarity linearization (CCL) algorithm. In the end, a numerical example involving a continuous stirred tank reactor (CSTR) system is described to prove the validity of the presented results.

Event-triggered Output Feedback Resilient Control for NCSs under Deception Attacks

This paper studies event-triggered output feedback resilient control for networked control systems (NCSs) under stochastic deception attacks following a Bernoulli distribution. Unlike continuous event-triggered mechanism (ETM) requiring dedicated hardware and complex Zeno-avoidance computation, an output-based discrete ETM is firstly introduced, which overcomes limits of continuous ETM and relaxes state-available constraint. Secondly, a novel time-delay system model is established, which makes it possible to study effects of the ETM, stochastic attacks and network-induced delays in a unified framework. Thirdly, less-conservative asymptotic stability criteria with desired H∞ index are obtained, which derive quantitative relationships among the ETM, stochastic attacks, network delays, plant and resilient controller. Further, sufficient conditions to co-deign the ETM and resilient controller are presented. Finally, examples confirm effectiveness of the proposed method.

Event-triggered finite-time H∞ filtering for networked systems under deception attacks

This paper is concerned with event-triggered H∞ filter design for a networked system suffering stochastic deception attacks in the sense of finite-time boundedness. Firstly, a networked filtering error model is well constructed by taking the effect of deception attacks and event-triggered scheme into account. Then, two sufficient conditions are derived to ensure that the resultant filtering error system is finite-time bounded with a prescribed H∞ performance, where the feasible H∞ filter parameters and the event-triggered communication parameters can be obtained in a unified framework. Finally, the effectiveness of proposed method is demonstrated through a tunnel diode circuit system.

Event-Triggered $H_\infty$ Load Frequency Control for Multiarea Power Systems Under Hybrid Cyber Attacks

This paper investigates the problem of event-triggered ${H_\infty }$ load frequency control (LFC) for multiarea power systems under hybrid cyber attacks, including denial-of-service (DoS) attacks and deception attacks. An event-triggered transmission scheme is developed under the DoS attacks to lighten the load of network bandwidth while preserving a satisfactory system performance. Then, a new switched system model accounting for the simultaneous presence of DoS attacks and stochastic deception attacks is established with respect to the LFC for multiarea power system. On the basis of the new model, sufficient conditions ensuring multiarea power system exponentially mean-square stable with prescribed ${H_\infty }$ performance are obtained by using Lyapunov stability theory. Furthermore, criteria for simultaneously designing the weighting matrix in event-triggered scheme and the controller gain matrix are derived by utilizing the linear matrix inequality technique. Finally, a three-area power system is simulated to demonstrate the usefulness of the approaches proposed in this paper.

Secure Load Frequency Control of Smart Grids under Deception Attack: A Piecewise Delay Approach

The problem of secure load frequency control of smart grids is investigated in this paper. The networked data transmission within the smart grid is corrupted by stochastic deception attacks. First, a unified Load frequency control model is constructed to account for both network-induced effects and deception attacks. Second, with the Lyapunov functional method, a piecewise delay analysis is conducted to study the stability of the established model, which is of less conservativeness. Third, based on the stability analysis, a controller design method is provided in terms of linear matrix inequalities. Finally, a case study is carried out to demonstrate the derived results.

Event-triggered distributed dynamic output-feedback dissipative control of multi-weighted and multi-delayed large-scale systems

This paper considers multi-weighted and multi-delayed large-scale interconnected systems, which have multiple coupling links between neighboring subsystems and all links have different coupling weights and delays. It describes an event-triggered distributed dynamic output-feedback control approach for dissipative stabilization of the concerned systems under quantization, packet dropouts and stochastic deception attacks. An event-triggered distributed dynamic output feedback controller (DOFC) is constructed and sufficient conditions are calculated for the exponential mean square stability along with a strict ( Q, S, R)-dissipative performance of the considered large-scale systems. The control gains for the subsystem controllers are determined by solving a nonlinear minimization problem using the cone complementarity linearization (CCL) algorithm. Finally, the obtained results are verified through a numerical example consisting of a continuous stirred tank reactor (CSTR) system.

Secure Distributed Finite-Time Filtering for Positive Systems Over Sensor Networks Under Deception Attacks.

This paper is concerned with secure l1 -gain performance analysis and distributed finite-time filter design for a positive discrete-time linear system over a sensor network in the presence of deception attacks. A group of intercommunicating sensors is densely deployed to measure, gather, and process the output of the positive system. Each sensor is capable of sharing its measurement with its neighboring sensors in accordance with a prescribed network topology while suffering from random communication link failure. Meanwhile, the aggregated measurement on each sensor during network transmission is corrupted by stochastic deception attacks which compromise the sensor's measurement integrity. First, a unified sensor measurement transmission model is put forward to account for the simultaneous presence of deception attacks and various network-induced constraints. Second, delicate secure distributed filters are constructed by admitting the corrupted sensor measurement. Third, theoretical analysis on finite-time l1 -gain boundedness of the filtering error system and design of desired positive filters are carried out. The solution to the filter gain parameters is characterized by a set of linear programming inequalities. Finally, the effectiveness of the obtained results is verified through the secure monitoring of power distribution in the smart grid.

Fusion estimation in clustering sensor networks under stochastic deception attacks

ABSTRACTIn this paper, a fusion estimation problem in clustering sensor networks under stochastic deception attacks is investigated. The sensors are divided into several clusters, and a local estimator is embedded in each cluster. During the network transmissions, deception attacks are considered to randomly occur and the statuses of the attacks are described by a set of Bernoulli variables. By using the clustering sampled information, a local minimum variance filter is derived and the filter gains are recursively determined. By using the local estimates and the local estimation error covariance matrices, a covariance intersection fusion algorithm is presented for the fusion centre to generate the final estimate. Moreover, the relationship between the trace of the local estimation error covariance matrix and the uniform successful attack rate is analysed. An illustrative example is given to shown the effectiveness of the proposed theoretical results.