Secure Control of Networked Switched Systems with Random DoS Attacks via Event-triggered Approach

Liu, Yonghui

doi:10.23919/ccc52363.2021.9550730

Cited by 2 publications

(5 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Next, to display the influences of the DoS parameters T and T min off , and to show the effect of T on system performance. We use the values of 𝛼 i , 𝜙 i , h, 𝜎, and 𝛾 in (43) and deal with the optimization problem for given distinct T: 25), subjects to LMIs (34), (38), and (39). (44) Table 1 gives the minimum values of T min off , the maximum allowable J ≜ (T − T min off )∕T × 100% called DoS attack rate, and 𝔏 2 − 𝔏 ∞ performance index 𝛾.…”

Section: Numerical Examplementioning

confidence: 99%

“…Notably, denial‐of‐service (DoS) attacks whose aim is to prevent signals transmission from arriving at their destination are the most probable type owing to they are easily implemented 36 . In order to eliminate the effect of DoS attacks, many efforts have been taken 37‐44 . In Reference 40, by integrating periodic DoS attacks, ETM, and sensor saturation, a new quantized state estimator for cyber‐physical systems was built.…”

Section: Introductionmentioning

confidence: 99%

“…36 In order to eliminate the effect of DoS attacks, many efforts have been taken. [37][38][39][40][41][42][43][44] In Reference 40, by integrating periodic DoS attacks, ETM, and sensor saturation, a new quantized state estimator for cyber-physical systems was built. Utilizing periodic DoS attacks model including action periods and sleeping periods, a switched filtering error system was established against DoS attacks in Reference 45.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Event‐triggered quantized L2−L∞$$ {\mathfrak{L}}_2-{\mathfrak{L}}_{\infty } $$ filtering for neural networks under denial‐of‐service attacks

Zhou

Chang

2022

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

This article deals with the reliable event‐triggered quantized frakturL2prefix−frakturL∞$$ {\mathfrak{L}}_2-{\mathfrak{L}}_{\infty } $$ filtering issue for neural networks with exterior interference under denial‐of‐service attacks. In order to lighten the load of communication channels and save network resources, a resilient event‐triggered mechanism and a quantization scheme are employed, simultaneously. By applying a piecewise Lyapunov–Krasovskii functional method, sufficient conditions containing limitations of denial‐of‐service attacks are derived to guarantee that the filter error system is exponentially stable as well as possesses a prescribed frakturL2prefix−frakturL∞$$ {\mathfrak{L}}_2-{\mathfrak{L}}_{\infty } $$ disturbance attenuation performance. Then, a co‐design method of the desired quantized frakturL2prefix−frakturL∞$$ {\mathfrak{L}}_2-{\mathfrak{L}}_{\infty } $$ filtering gain matrix and event‐triggering parameter can be obtained provided that the linear matrix inequalities have a feasible solution. Finally, the usefulness of the proposed design method is demonstrated by a numerical example.

show abstract

Section: Numerical Examplementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Event‐triggered quantized L2−L∞$$ {\mathfrak{L}}_2-{\mathfrak{L}}_{\infty } $$ filtering for neural networks under denial‐of‐service attacks

Zhou

Chang

2022

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

show abstract

“…The results of cyber attacks on the switched systems can be seen in References 22‐28. Literature 22 studies the effect of jamming attacks on the stochastic switched systems.…”

Section: Introductionmentioning

confidence: 99%

“…Hence, networked security control subject to DoS attacks has drawn considerable attention. Assume that DoS attacks randomly occur obeying to the Bernoulli distribution, security control methods are designed in References 25 and 26. By proposing multiple quadratic Lyapunov functions with the merged switching signal, an event‐triggered

H_{\infty}

controller is designed in Reference 27.…”

Section: Introductionmentioning

confidence: 99%

Quantized stabilization of switched systems with partly unstabilizable subsystems and denial‐of‐service attacks

Yan

Xia

Wang

et al. 2022

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

This article addresses the problem of stabilizing a continuous-time switched system affected by quantization and denial-of-service (DoS) attacks. The switching is assumed to be slow enough in the sense of combined dwell time and average dwell time, individual modes are assumed to be partly unstabilizable, and DoS attacks are supposed as energy limited by restraining DoS frequency and DoS duration. By introducing a Decision Maker into the system framework and proposing a switching algorithm for the attacked intervals, we simplify the design rules of the controller and divide the system status into four cases.On the basis of approximating the reachable set and analyzing the increasing/decreasing rate of Lyapunov function for each case, the sufficient conditions ensuring the exponential convergence and Lyapunov stability of the closed-loop system are obtained. Two examples are illustrated to demonstrate the effectiveness of the theoretical analysis.

show abstract

Secure Control of Networked Switched Systems with Random DoS Attacks via Event-triggered Approach

Cited by 2 publications

References 20 publications

Event‐triggered quantized L2−L∞$$ {\mathfrak{L}}_2-{\mathfrak{L}}_{\infty } $$ filtering for neural networks under denial‐of‐service attacks

Event‐triggered quantized L2−L∞$$ {\mathfrak{L}}_2-{\mathfrak{L}}_{\infty } $$ filtering for neural networks under denial‐of‐service attacks

Quantized stabilization of switched systems with partly unstabilizable subsystems and denial‐of‐service attacks

Contact Info

Product

Resources

About