Stability Of Cyber-physical System Research Articles

Switching LPV approach for analysis and control of TCP-based cyber-physical systems under DoS attack

Cyber-physical systems (CPSs) integrate controllers, sensors, actuators, and communication networks. Tight integration with communication networks makes CPSs vulnerable to cyberattacks. In this paper, the impact of denial of service (DoS) attacks on the stability of cyber physical systems is investigated, with a focus on the transmission control protocol (TCP). A sufficient stability condition is extracted in linear matrix inequality (LMI) form. The TCP-CPS under DoS attack is modeled as a switching linear parameter-varying (LPV) time-delay system using the Markov jump model. Subsequently, a parameter-dependent stabilizing controller is designed for CPSs under DoS attacks, taking into account network parameters. Finally, the efficiency and feasibility of the findings are demonstrated through a well-known case study in the networked control systems literature.

Information fusion architecture for secure cyber physical systems

The security essentially governs the usability and stability of Cyber Physical Systems (CPSs) whose cyber and physical components of the system are integrated. Security solutions to this effect are threefold - detecting attacks, preventing them and finally, maintaining system integrity under attacks. In this paper, we provide a solution to the problem of detecting collaborative attacks by proposing an information fusion architecture, which utilizes the strengths of Bayesian estimation in determining causalities as conditional probabilities. We propose a Time-Varying Dynamic Bayesian Network (TVDBN) to ascertain system state information, eventually enabling the system administrator to make control decisions and maintain system stability under security attacks. The control information to the physical components such as actuators is sent over by the sensors, which are the cyber components. As such, the focus of this paper is to provide a solution to uphold the stability of a CPS based on control theoretic aspects that can be adversely affected by compromised cyber components. Theoretical aspects touched in this paper for this purpose are - bounds on transmission delays, quantization errors and sampling time. Using our proposed information fusion architecture, we were able to detect the presence of both, the stand-alone and collaborative attacks on the CPS. Our experimental results showed that our fusion architecture can detect collaborative attacks and profile them with an average accuracy of 91.7%. Given the difficulty in detecting the presence of collaborative attacks in CPS, this level of accuracy is considered high to protect CPS applications.

PDF‐based tuning of stochastic optimal controller design for cyber‐physical systems with uncertain delay dynamics

Uncertain dynamics in communication network, including random delays and packet losses make it difficult to guarantee stability of cyber-physical systems (CPSs). Many existing works consider the uncertainties of network channel with strong assumptions that network delay bounds and its distribution are known a priori and time-invariant. However, these assumptions could be invalidated in realistic CPSs by malicious attacks, system hardware faults, topology changes etc. A probability density function (PDF)-based tuning of stochastic optimal control (PTSOC) is proposed to manage the unknown dynamics in the embedded network. The update law of the proposed controller is derived and updated based on the PDF estimation of network delays that explicitly consider delays and its time-varying distribution. The results illustrate that the proposed PTSOC has a better performance in terms of the overshoot, convergence time, and cost when compared with the conventional stochastic optimal control.