INCREMENTAL FAULT DIAGNOSABILITY AND SECURITY/PRIVACY VERIFICATION

Dynamical systems can be classified into two groups. One group is continuoustime systems that describe the physical system behavior, and therefore are typically modeled by differential equations. The other group is discrete event systems (DES)s that represent the sequential and logical behavior of a system. DESs are therefore modeled by discrete state/event models.DESs are widely used for formal verification and enforcement of desired behaviors in embedded systems. Such systems are naturally prone to faults, and the knowledge about each single fault is crucial from safety and economical point of view. Fault diagnosability verification, which is the ability to deduce about the occurrence of all failures, is one of the problems that is investigated in this thesis. Another verification problem that is addressed in this thesis is security/privacy. The two notions currentstate opacity and current-state anonymity that lie within this category, have attracted great attention in recent years, due to the progress of communication networks and mobile devices.Usually, DESs are modular and consist of interacting subsystems. The interaction is achieved by means of synchronous composition of these components. This synchronization results in large monolithic models of the total DES. Also, the complex computations, related to each specific verification problem, add even more computational complexity, resulting in the well-known state-space explosion problem.To circumvent the state-space explosion problem, one efficient approach is to exploit the modular structure of systems and apply incremental abstraction. In this thesis, a unified abstraction method that preserves temporal logic properties and possible silent loops is presented. The abstraction method is incrementally applied on the local subsystems, and it is proved that this abstraction preserves the main characteristics of the system that needs to be verified.The existence of shared unobservable events means that ordinary incremental abstraction does not work for security/privacy verification of modular DESs. To solve this problem, a combined incremental abstraction and observer generation is proposed and analyzed. Evaluations show the great impact of the proposed incremental abstraction on diagnosability and security/privacy verification, as well as verification of generic safety and liveness properties. Thus, this incremental strategy makes formal verification of large complex systems feasible

Diagnosability Verification Using Compositional Branching Bisimulation

This paper presents an efficient diagnosability verification technique, based on a general abstraction approach. More specifically, branching bisimulation including state labels with explicit divergence (BBSD) is defined. This bisimulation preserves the temporal logic property that verifies diagnosability. Based on a proposed BBSD algorithm, compositional abstraction for modular diagnosability verification is shown to offer a significant state space reduction in comparison to state-of-the-art techniques. This is illustrated by verifying non-diagnosability analytically for a set of synchronized components, where the abstracted solution is independent of the number of components and the number of observable events

Verification of diagnosability based on compositional branching bisimulation

This paper presents an efficient diagnosability verification technique, based on a general abstraction approach. We exploit branching bisimulation with explicit divergence (BBED), which preserves the temporal logic property that verifies diagnosability. Furthermore, using compositional abstraction for modular diagnosability verification offers additional state space reduction in comparison to the state-of-the-art techniques

A survey on efficient diagnosability tests for automata and bounded Petri nets

This paper presents a survey and evaluation of the efficiency of polynomial diagnosability algorithms for systems modeled by Petri nets and automata. A modified verification algorithm that reduces the state space by exploiting symmetry and abstracting unobservable transitions is also proposed. We show the importance of minimal explanations on the performance of diagnosability verifiers. Different verifiers are compared in terms of state space and elapsed time. It is shown that the minimal explanation notion involved in the modified basis reachability graph, a graph presented by Cabasino et al. [3] for diagnosability analysis of Petri nets, has great impact also on automata-based diagnosability methods. The evaluation often shows improved computation times of a factor 1000 or more when the concept of minimal explanation is included in the computation

Verification of diagnosability based on compositional branching bisimulation

This paper presents an efficient diagnosability verificationtechnique, based on a general abstraction approach.We exploit branching bisimulation with explicitdivergence (BBED), which preserves the temporal logicproperty that verifies diagnosability. Furthermore, usingcompositional abstraction for modular diagnosability verificationoffers additional state space reduction in comparisonto the state-of-the-art techniques

Incremental Abstraction for Diagnosability Verification of Modular Systems

In a diagnosability verifier with polynomial complexity, a non-diagnosable system generates uncertain loops. Such forbidden loops are in this paper transformed to forbidden states by simple detector automata. The forbidden state problem is trivially transformed to a nonblocking problem by considering all states except the forbidden ones as marked states. This transformation is combined with one of the most efficient abstractions for modular systems called conflict equivalence, where nonblocking properties are preserved. In the resulting abstraction, local events are hidden and more local events are achieved when subsystems are synchronized. This incremental abstraction is applied to a scalable production system, including parallel lines where buffers and machines in each line include some typical failures and feedback flows. For this modular system, the proposed diagnosability algorithm shows great results, where diagnosability of systems including millions of states is analyzed in less than a second

Visible Bisimulation Equivalence - A Unified Abstraction for Temporal Logic Verification

Bisimulation is an abstraction method that can be used to reduce the number of states fortransition systems. This paper presents an alternative formulation of bisimulation, directly based on anequivalence relation and partitioning of the state space. The formulation, here called visible bisimulationequivalence, unifies stuttering and branching bisimulation by including both state and event labels inthe abstraction. The proposed divergence-sensitive visible (DSV) bisimulation equivalence is shown tobe equivalent to a temporal logic called ECTL, where CTL is extended with events. This means thatDSV bisimulation equivalence preserves most temporal temporal logic properties that are of interest.The proposed bisimulation abstraction is applied to a set of synchronized submodels, where localevents are identified incrementally and abstracted after each synchronization. Since the bisimulationreduction is applied after each synchronization, a significant part of the state space explosion in ordinarysynchronization is avoided. Since the abstraction is polynomial in the number of states and transitions,this is an attractive method for verification and synthesis based on temporal logic