Secret inference and attacktability analysis of discrete event systems

This paper aims at defining a model-driven approach for the diagnosability analysis of discrete event systems (DES). The proposed approach can be adopted during the design of modern control systems, in which many sensors and actuators are employed and the diagnosability of faults within a certain delay could be an issue. The proposal represents a first step towards an automatic model-driven process which derive formal models from a complete high-level specification of DESs. The specification activity of our approach relies on the Dynamic STate Machine (DSTM) formalism, a new language that extends state machines with dynamic instantiation, interrupts and asynchronous communication. The paper will describe how we can automatically derive Petri net and Promela models from the high-level DSTM specification. The former model can be used to apply diagnosability analysis approaches proposed in the DES community, while the latter can be used to apply model checking techniques. An application of the proposed model-driven approach is described by deriving both a PN and a Promela model for the well-known railway level crossing benchmark.

Petrinets are the suitable tool for modeling and analysis of discrete event systems. The effective methods of analyzing the discrete event systems (DES) are exhibited by Petri nets. The entire structure of the system is mathematically expressed using Petrinets and also all the properties are analysed by different methods. The properties of Petrinets are different in various systems, a Flexible Manufacturing System (FMS) requires production activities in which raw materials, energy, labour, and equipment are combined together in the modification process for the production of good quality goods.” The word “flexible” explains the capability of the system to relate productively to make changes in the system. These changes can be internal failure of the system or classification problems such as a sample or external changes in the structure of the model as well as demand for the process. The inherent limitations such as undecidable properties, complexity in checking, automatic verification of the modeled system are existing in FMS. This paper explains a study on FMS using Petri net reduction. A PN underlies event structures with casuality and compatibility relations. Partial order methods and reduction methods reduce the complexity of constructing the reachability graph. The determination of PN system through reduction methods in recent years focused by many researchers. The significance of reduction methods are highlighted to execute the faster analysis of a system. Instead of coverability trees and the graphical representation the incidence matrix of the PNs are used for the reduction methods. Reduction methods are used to simplify large scale PNs into “equivalent” smaller nets. Boundedness, liveness, simplification of implicit places, shared resources and elimination of self-loops are checked though equivalent smaller nets. The structure of FMS is preserved.

For over twenty years, hybrid systems, involving both a discrete-valued state component and a continuous-valued state component (evolving in either discrete or continuous time), have challenged control engineers interested in expanding the applications of control theory. In particular, the hybrid system representation has motivated the formulation of "fault-tolerant" optimal control problems for systems subject to abrupt changes in their structure, parameters or operating environment. One approach has been the development of optimal controllers for jump linear systems. Strong theoretical results are currently limited, however, to Markov and semi-Markov jump processes, when change in the system structure are perfectly observed. During the same two decades, theory and methods for the analysis of discrete event systems have been developed. Recently the control of discrete event systems has received significant attention. This paper is directed toward the application of jump systems control theory to the control of continuous variable processes driven by discrete event systems.

A GSPN-Based automatic analysis tool for discrete event systems

In this paper, two approaches for diagnosability analysis of discrete event systems are discussed and experimentally evaluated. The considered approaches are the diagnoser-based approach proposed in [1, 2] and the model-checking reformulation approach proposed in [3, 4]. Experiments are performed on a level crossing benchmark, using the software tools integrating the considered approaches. These two approaches show different features in terms of state-space building and procedure for analyzing diagnosability. Based on the obtained results through the benchmark, a comparative discussion is provided particularly regarding the generated state-spaces and the time consumption for analyzing diagnosability.

The paper deals with the definition of procedure that enables one to determine, for a given plant, if all faults can be detected and located after a finite sequence of observable events. More formally, the diagnosability is the property that every fault can be correctly detected from the observable events of the system after its occurrence no later than a bounded number of events. In this paper, the diagnosability problem of Discrete Event Systems (DESs) is studied. As modeling tool, finite-state automaton in an event-based framework is used. A necessary and sufficient condition of diagnosability of such systems is proposed. The results proposed in this paper allow checking the diagnosability of discrete event systems in an efficient way, i.e. in polynomial time.

This article deals with the analysis of discrete event systems which can be modelled by timed event graphs with multipliers (TEGMs). These graphs are an extension of weighted T-systems studied in the Petri net literature. These models do not admit a linear representation in (min, +) algebra. This nonlinearity is due to the presence of weights on arcs. To mitigate this problem of nonlinearity and to apply some basic results used to analyse the performances of linear systems in dioid algebra, we propose a linearisation method of mathematical model reflecting the behaviour of a TEGM in order to obtain a (min, +) linear model.

Min-max functions are dynamic programming operators of zero-sum deterministic games with finite state and action spaces. The problem of computing the linear growth rate of the orbits (cycle-time) of a min-max function, which is equivalent to computing the value of a deterministic game with mean payoff, arises in the performance analysis of discrete event systems. We present here an improved version of the policy iteration algorithm given by Gaubert and Gunawardena in 1998 to compute the cycle-time of a min-max functions. The improvement consists of a fast evaluation of the spectral projector which is adapted to the case of large sparse graphs. We present detailed numerical experiments, both on randomly generated instances, and on concrete examples, indicating that the algorithm is experimentally fast.

Companies have been forced to collaborate with each other, sharing knowledge, adopting and applying better practices of product design and manufacturing, and exploring internet-based applications. This collaborative activity is established in the context of productive processes, properly described. In other words, the steps of the productive process should be described in a language that could be interpreted by the production equipment of different collaborators (companies that are part of this new organization). However, the available languages for describing the processes today do not consider heterogeneous environments with heterogeneous productive resources (equipment, tools, devices and others from different manufacturers, for example). On the other hand, there are formal methods that allow extensions that make them able to describe and interpret the productive operations sequence. One of such tools is the Petri net, which is used in the modeling and analysis of discrete event systems. Thus, a notation is proposed, based on Petri net, for the description of productive processes in a collaborative environment.

Identification of labeled Petri nets from finite automata

In this paper, we investigate how to quantitatively evaluate the performance of state estimation in a discrete event system. We adopt stochastic automaton to quantitatively describe a discrete event system. With the stochastic automaton, we can calculate the probability of occurrence of any event sequence. We say that an event sequence (with sufficient length) is detectable if we can determine the current state and subsequent states of the system after the occurrence of the sequence. We then define the sum of probabilities of all detectable event sequences as a quantitative state estimation indicator. This indicator is the limit when the length of sequence goes to infinite. In order to calculate the limit, we augment the discrete event system into a larger automaton which includes the information of the discrete event system and all its state estimates. The augmented automaton is also a stochastic automaton and can be converted into a Markov Chain by removing all the event labels. The calculation of the limit is then translated into the calculation of the sum of probabilities of some states in the Markov Chain, which can be done efficiently.

In the conventional framework for failure diagnosis of partially observed discrete event systems, it is assumed that, for each event, the corresponding output symbol is determined uniquely. However, this assumption does not hold in discrete event systems such as a mobile system, where an output symbol depends on not only an event but also a state at which the event occurs. In this paper, we model such discrete event systems by Mealy automata with nondeterministic output functions, and consider a decentralized failure diagnosis problem that requires any occurrence of a failure should be detected by at least one local diagnoser within a uniformly bounded number of steps. We present a necessary and sufficient condition for the existence of a decentralized diagnoser. We then present an algorithm for verifying this condition. Moreover, we present a method for synthesizing local online diagnosers.

Diagnosability of Discrete Event Systems under Sensor Attacks*

Petri net models are used to detect and isolate faults in case of discrete event systems as manufacturing, robotic, communication and transportation systems. This chapter addresses two problems. The first one is the structure designs and parameters identification of the Petri net models according to the observation and analysis of the sequences of events that are collected. Deterministic and stochastic time Petri nets are concerned. The proposed method is based on a statistical analysis of data and has a practical interest as long as sequences of events are already saved by supervision systems. The second problem concerns the use of the resulting Petri net models to detect, isolate and characterize faults in discrete event systems. This contribution includes the characterization of intermittent faults. This issue is important because faults are often progressive from intermittent to definitive and early faults detection and isolation improve productivity and save money and resources.

The Internet Engineering Task Force (IETF) has defined routing protocols for low power and lossy networks (RPL) for constrained devices. RPL constructs DODAGs (destination oriented directed acyclic graphs), to optimize routing. RPL ensures acyclic topology with the DODAG version number. However, the control message’s DODAG version number is not authenticated. So, RPL is vulnerable to network resource attack known as DODAG Version Number (DVN) attack. DVN attack creates a packet delay, packet loss, cyclic topology, etc., in the network. This paper proposes a method for detecting DODAG version number attacks. Several existing schemes to defend against the DVN, such as cryptographic techniques, trust-based, threshold-based and mitigation are computationally intensive or require protocol modification. DVN does not change the packet format or sequence of packets, but can still perform attacks and hence fall under the category of stealthy attacks, which are difficult to detect using traditional intrusion detection system’s (IDS). Discrete-event system (DES) based IDS have been applied in the literature for stealthy attacks that achieve low overhead, low false alarm rate, etc. However, the construction of DES-based IDS for network protocol may lead to errors, as modelling is manual. The resulting IDS, therefore, is unable to guarantee its correctness. This paper proposes linear temporal logic (LTL) based DES paradigm to detect DVN. LTL-based paradigm facilitates formal verification of the DES-based IDS, and hence the correctness of the scheme is ascertained. The proposed technique is simulated using the Contiki cooja simulator. When the percentage of spiteful nodes in the network increases, the true positive rate, and packet delivery rate drops, while the false positive rate and control message overhead increase. The memory requirement for sending the packets and verifying the nodes is minimal. The LTL-based IDS has been formally verified using NuSMV to ensure the correctness of the framework.