Parameter and Insertion Function Co-synthesis for Opacity Enhancement in Parametric Stochastic Discrete Event Systems

Abstract

Opacity is a property that characterizes the system's capability to keep its "secret" from being inferred by an intruder that partially observes the system's behavior. In this paper, we are concerned with enhancing the opacity using insertion functions, while at the same time, enforcing the task specification in a parametric stochastic discrete event system. We first obtain the parametric Markov decision process that encodes all the possible insertions. Based on which, we convert this parameter and insertion function co-synthesis problem into a nonlinear program. We prove that if the output of this program satisfies all the constraints, it will be a valid solution to our problem. Therefore, the security and the capability of enforcing the task specification can be simultaneously guaranteed.

Towards approximate opacity of cyber-physical system

“…The above mentioned works mainly consider DES modeled by finite-state automata. More recently, the definitions and verification algorithms for different notions of opacity have been extended to other classes of (discrete) systems, including Petri nets [TLSG17a,TLSG17b,CFML18,BDT18], stochastic systems [SH14, KH18,WLL18], recursive tile systems [CMPM14] and pushdown systems [KH13]. The interested readers are referred to recent surveys [JLF16,LLH18] for more references and recent developments on this active research area.…”