Search

This paper addresses the problem of cyber-attack detection in a discrete event system by proposing a novel model. The model utilizes graph convolutional networks to extract spatial features from event sequences. Subsequently, it employs gated recurrent units to re-extract spatio-temporal features from these spatial features. The obtained spatio-temporal features are then fed into an attention model. This approach enables the model to learn the importance of different event sequences, ensuring that it is sufficiently general for identifying cyber-attacks, obviating the need to specify attack types. Compared with traditional methods that rely on synchronous product computations to synthesize diagnosers, our deep learning-based model circumvents state explosion problems. Our method facilitates real-time and efficient cyber-attack detection, eliminating the necessity to specifically identify system states or distinguish attack types, thereby significantly simplifying the diagnostic process. Additionally, we set an adjustable probability threshold to determine whether an event sequence has been compromised, allowing for customization to meet diverse requirements. Experimental results demonstrate that the proposed method performs well in cyber-attack detection, achieving over 99.9 % accuracy at a 1 % threshold and a weighted F1-score of 0.8126, validating its superior performance. [ABSTRACT FROM AUTHOR]

This paper presents some graph-theoretic conditions for a democratic system controlled by a social network to converge to a regressive or progressive system over time. The democratic system is modeled as a finite state automaton, and a social network of agents is modeled as a directed graph. Agents are controllers making decisions to enable or disable events such that their objectives are to be met. Based on the individual decisions of agents, the final decision is made by the majority rule. Specifically, the conditions obtained imply two strategies for the groups of regressive or progressive agents to achieve their objectives: one is to prevent informed agents in other groups from influencing uninformed agents, and the other is to make at least one uninformed agent in every cycle follow the decisions of the group. [ABSTRACT FROM AUTHOR]

The supervisory control of Petri nets aims to enforce the undesired behavior as unreachable by designing a set of control places. This work presents a set cover approach to design maximally permissive supervisors. For each first-met bad marking, an integer linear programming problem is developed to obtain a control place to prohibit it. An objective function is formulated to make the maximal number of first-met bad markings forbidden. Then, we develop a set covering approach to minimize the number of selected control places. The proposed approach can guarantee the maximal permissiveness of the obtained supervisor and provide a trade-off between structural complexity and computational cost. Several examples are considered to validate the proposed method. [ABSTRACT FROM AUTHOR]

Copyright of Information & Control is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Industrial control systems (ICS) require system design and operation under cyber-attacks. This study aims to design a fallback control system that can switch from normal control to fallback control and verify its superiority. The target system is a factory automation (FA) system consisting of a normal programmable logic controller (PLC) and a fallback PLC. In this system, we design a fallback logic that takes over control in the case of cyber-attacks. The design of this logic requires a system model that manages smooth state transitions between normal control and fallback control in an integrated manner under cyber-attacks. In response, we model a control program in the framework of discrete event systems (DESs) and apply supervisory control to derive a supervisor model that can manage the system in an integrated manner. To ensure the controllability of the FA system during cyber-attacks, we design a control specification that includes a detection function to enable rapid switching of the control state. As a result, we generate the fallback logic from the supervisor model with guaranteed controllability under cyber-attacks and implement it in a fallback PLC to verify the effectiveness of the proposed logic. [ABSTRACT FROM AUTHOR]

The article is devoted to the development of an approach to solving the main problems of the theory of supervisory control of logical discrete-event systems (DES), based on their representation in the form of positively constructed formulas (PCF). We consider logical DESs in automata form, understood as generators of some regular languages. The PCF language is a complete first-order language, the formulas of which have a regular structure of alternating type quantifiers and do not contain a negation operator in the syntax. It was previously proven that any formula of the classical first-order predicate calculus can be represented as a PCF. PCFs have a visual tree representation and a natural question-and-answer procedure for searching for an inference using a single inference rule. It is shown how the PCF calculus, developed in the 1990s to solve some problems of control of dynamic systems, makes it possible to solve basic problems of the theory of supervisory control, such as checking the criteria for the existence of supervisory control, automatically modifying restrictions on the behavior of the controlled system, and implementing a supervisor. Due to some features of the PCF calculus, it is possible to use a non-monotonic inference. It is demonstrated how the presented PCF-based method allows for additional event processing during inference. The Bootfrost software system, or the so-called prover, designed to refute the obtained PCFs is also presented, and the features of its implementation are briefly described. As an illustrative example, we consider the problem of controlling an autonomous mobile robot.

Copyright of Automatisierungstechnik is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the context of extended probabilistic automata, this study focuses on an information flow property, called opacity, of discrete event systems. The achievement of this research is the formulation and in-depth analysis of what is termed sequential k-opacity. This metric, through its detailed assessment, marks an explicit and visible advancement beyond the existing paradigms for measuring system opacity. It introduces an improved method for analyzing the probability of event sequences leading to confidential states within a system. An approach of such a comprehensive nature is essential for a detailed analysis of opacity in systems typified by deterministic and stochastic elements. Furthermore, this work incorporates a numerical case study that provides a baseline for further investigations in practical applications, thereby validating the proposed framework’s usefulness. The research progresses to explore novel approaches to the reinforcement and persistence of system opacity within extended probabilistic automata. Among these approaches, the strategic use of fake events is critical as it is a fundamental tool for enhancing system security and secrecy, which plays an important role in protecting sensitive and secret data by effectively hiding the real status of the system from outside inspection.

Deadlocks are of paramount importance in resource allocation systems, which are usually treated from the perspective of discrete event systems. This paper develops a deadlock prevention strategy for a system modeled with Petri nets, by endowing appropriate time constraints with certain transitions to schedule the firing priority of enabled transitions in a Petri net such that transition sequences leading to deadlocks are prohibited, i.e., expanding an untimed Petri net model into a time Petri net to prevent deadlocks. To increase the system permissiveness of a time Petri net with time constraints endowed, a control place is designed, which does not expand the reachable space of the original Petri net. The predominant role of the control place is to convert continuously enabled transitions at certain markings into newly enabled transitions, which can prolong the firing time of transitions. Furthermore, we propose a method that merely enumerates deadlock prevention condition inequalities to derive a series of time constraints by probing the connection between deadlock prevention conditions and transitions. The developed method only needs to designate time constraints for partial transitions. Examples are provided to demonstrate the effectiveness of the presented methodology.

Program deadlock detection plays an important role in ensuring the stability of software systems. In view of the high efficiency and low false alarm rate, dynamic deadlock analysis methods are widely studied. However, existing dynamic analysis methods use lock graph or its extended variants to model program behavior. Since there are information loss in existing lock graphs, deadlock false positives still exist. To solve the problem, a novel 2-stage dynamic deadlock analysis method is proposed. In the first stage, a Petri net model of the program is constructed by analyzing program running traces. Then, unfolding-based Petri net dead marking detection methods are used to identify potential program deadlocks. In the second stage, based on Petri net unfolding techniques, a deterministic program scheduling scheme that can be used for deadlock replay is derived for each potential deadlock. Each successfully replayed program deadlock is a real deadlock. It is shown that the proposed deadlock detection and replay method can eliminate more false positives compared to general dynamic methods, and the deadlock replay scheme is deterministic and easy to understand compared with existing random scheduling strategies.

This paper addresses the problem of cyber-attack detection in a discrete event system by proposing a novel model. The model utilizes graph convolutional networks to extract spatial features from event sequences. Subsequently, it employs gated recurrent units to re-extract spatio-temporal features from these spatial features. The obtained spatio-temporal features are then fed into an attention model. This approach enables the model to learn the importance of different event sequences, ensuring that it is sufficiently general for identifying cyber-attacks, obviating the need to specify attack types. Compared with traditional methods that rely on synchronous product computations to synthesize diagnosers, our deep learning-based model circumvents state explosion problems. Our method facilitates real-time and efficient cyber-attack detection, eliminating the necessity to specifically identify system states or distinguish attack types, thereby significantly simplifying the diagnostic process. Additionally, we set an adjustable probability threshold to determine whether an event sequence has been compromised, allowing for customization to meet diverse requirements. Experimental results demonstrate that the proposed method performs well in cyber-attack detection, achieving over 99.9% accuracy at a 1% threshold and a weighted F1-score of 0.8126, validating its superior performance.

In the realm of data protection strategies, differential privacy ensures that unauthorized entities cannot reconstruct original data from system outputs. This study explores discrete event systems, specifically through probabilistic automata. Central is the protection of state data, particularly the initial state privacy of multiple starting states. We introduce an evaluation criterion to safeguard initial states. Using advanced algorithms, the proposed method counters the probabilistic identification of any state within this collection by adversaries from observed data points. The efficacy is confirmed when the probability distributions of data observations tied to these states converge. If a system's architecture does not meet state differential privacy demands, we propose an enhanced supervisory control mechanism. This control upholds state differential privacy across all initial states, maintaining operational flexibility within the probabilistic automaton framework. Concluding, a numerical analysis validates the approach's strength in probabilistic automata and discrete event systems. [ABSTRACT FROM AUTHOR]

This paper presents an approach to solve the least-cost transition sequences estimation problem in labelled time Petri net (LTPN) systems with unobservable transitions. Particularly, the considered LTPN system is bounded, in which each transition has a nonnegative cost and is labelled as either observable or unobservable. We first introduce a graph, called a segmented modified state class graph (SMSCG), that is a compact representation of the partial state space of an LTPN system. Based on the SMSCG and an observed time-label sequence, a method to estimate logic consistent transition sequences is proposed. By exploiting the transitions-related timing constraints in SMSCGs, a procedure for determining which logic consistent transition sequences are timing consistent with the observed time-label sequence and a given time is reported. Finally, we develop an algorithm to perform the estimation of least-cost transition sequences. [ABSTRACT FROM AUTHOR]

The supervisory control of Petri nets aims to enforce the undesired behavior as unreachable by designing a set of control places. This work presents a set cover approach to design maximally permissive supervisors. For each first-met bad marking, an integer linear programming problem is developed to obtain a control place to prohibit it. An objective function is formulated to make the maximal number of first-met bad markings forbidden. Then, we develop a set covering approach to minimize the number of selected control places. The proposed approach can guarantee the maximal permissiveness of the obtained supervisor and provide a trade-off between structural complexity and computational cost. Several examples are considered to validate the proposed method.

This paper proposes a controller synthesis method based on matrix transformation and integer linear programming to address the problem of forbidden state controller design for Petri net systems with uncontrollable transitions. The key idea behind this method involves transforming generalized mutual exclusion constraints (GMEC) that represent the legal states of a Petri net system. Based on the incidence matrix of a Petri net, it divides the set of places into irrelevant places, uncontrollable places, and complementary places. By modifying the weights of complementary places and uncontrollable places in the given GMEC, it then converts the given GMEC into an allowable one by solving integer linear programming problems. Using the allowable GMEC, this paper designs a structural controller for Petri nets based on the principle of place invariants. Finally, it takes a part processing system as an example to show that the application is versatile and efficient, offering an effective solution for the controller design of intelligent manufacturing systems. [ABSTRACT FROM AUTHOR]

This paper considers the verification of decentralized fault pattern diagnosability for discrete event systems, where the pattern is modeled as a finite automaton whose accepted language is the objective to be diagnosed. We introduce a notion of codiagnosability to formalize the decentralized fault pattern diagnosability, which requires the pattern to be detected by one of the external local observers within a bounded delay. To this end, a structure, namely a verifier, is proposed to verify the codiagnosability of the system and the fault pattern. By studying an indeterminate cycle of the verifier, sufficient and necessary conditions are provided to test the codiagnosability. It is shown that the proposed method requires polynomial time at most. In addition, we present an approach to extend the proposed verifier structure so that it can be applied to centralized cases. [ABSTRACT FROM AUTHOR]

Information security is an important area of concern in modern computer-integrated systems. It involves implementing preventative measures to protect confidential data from potential vulnerabilities, such as unauthorized access, secret disclosure, modification, or destruction. Considering such threats, we investigate a particular confidentiality property called opacity, which specifies a system's ability to cover its 'secret' data from being interfered with by outside observers, termed as intruders. This paper discusses language-based opacity formulation and verification in the context of discrete event systems represented by partially observed Petri nets. In this context, we identify two opacity properties, called consistency and non-secrecy; then, we exploit the mathematical characterization of a net system, to separately check each property, by specifying two feasibility problems. The proposed method is carried out for two distinct settings of a system. The first setting is centralized, where an intruder is granted complete information about the system structure but a partial observation of its behavior. The second setting is decentralized, where a group of intruders cooperates to reveal the secret language, by using a coordinator. Finally, experimental findings are given, to demonstrate the proficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper investigated the verification of detectability for discrete event systems based on a class of partially observed unbounded Petri nets. In an unbounded net system, all transitions and partial places are assumed to be unobservable. The system administrator can only observe a few observable places, i.e., the number of tokens at these places can be observed, allowing for the estimation of current and subsequent states. The concepts of quasi-observable transitions, truly unobservable transitions, and partial markings are used to construct a basis coverability graph. According to this graph, four sufficient and necessary conditions of detectability are proposed. Correspondingly, a specific example is proposed to prove that the detectability can be verified in the unbounded net system. Furthermore, based on the conclusion of detectability, the system's ability to detect critical states was explored by using the basis coverability graph, called C-detectability. Two real-world examples are proposed to show that the detectability of discrete event systems has not only pioneered new research methods, but also demonstrated that the real conditions faced by this method are more general, and it has overcome the limitations of relying only on the ideal conditions of bounded systems for verification. [ABSTRACT FROM AUTHOR]

People's lifestyle, especially in shopping, has shifted from offline shopping, such as in supermarkets, traditional markets, stalls, and so on, to online shopping. Therefore, online business (ecommerce) has increased, resulting in a surge in the business potential of freight forwarder companies. When there is an increase in demand for the delivery of goods by sellers to consumers, companies need to make adjustments to improve their performance. This paper proposed the sequence of goods delivery services for XYZ companies by considering dynamic requests and conditions that vary discretely over time. This paper is based on a case company in Bandung, Indonesia. The method employed queuing models and discrete event simulations using hypothetical data with performance criteria to minimize the total cost of shipping goods. Simulations are carried out using one courier and one zone to compare customer service determination algorithms, namely first-come, first-served, proximity, and predictive control models. The simulation results show that the proximity algorithm produces a minimum total cost of Rp 1,785,749, the smallest cost compared to using first-come, first-served and predictive control models, respectively IDR 2,782,389, and IDR 2,639,291. Then, the Annova test was conducted, which provided information that one policy differed significantly from another, and a Turkey test was carried out, showing that the proximity algorithm produces better performance than other algorithms. The contribution of this paper is to present that the delivery service employed by the company provided a minimum total cost. [ABSTRACT FROM AUTHOR]

Diagnosability of a discrete event system is usually dealt at the system level entailing synchronous composition of component automata leading to state explosion problem. However, many of the systems are modular in nature allowing localized detection and isolation of faults. Moreover, developments in sensor technology allow direct detection of faults based on sensor output which are denoted as observations in this paper. Combining modularity and observations, we propose a new concept of O-diagnosability based on observations at the subsystem or component level to make the diagnosability verification less complex. The concepts of monolithic (system) O-diagnosability and CO-diagnosability (system to component) are introduced and necessary and sufficient conditions for O-diagnosability are derived. Theoretical results on the relation between monolithic O-diagnosability and CO-diagnosability support the system level diagnosability verification through component level analysis in a progressive way. Computational complexity for the proposed diagnosability verification is shown to be of the order of n2 where n is the largest number of diagnoser states of a component of the system. [ABSTRACT FROM AUTHOR]

Copyright of Information & Control is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The diagnosability problem has been extensively studied over the past two decades for discrete event systems associated with intermittent faults. Diagnosability is a property that requires a large number of sensors for fault detection, which leads to expensive system deployment. To alleviate the above drawbacks, we propose a new property called intermittent fault manifestability, which is a weaker observation requirement for diagnosing the occurrence of intermittent faults. In order to verify the property, we consider fault events and their corresponding reset events and introduce two properties of f-manifestability and r-manifestability, respectively. Based on an intermittent fault pattern automaton, we first propose a diagnoser structure to track the occurrence of intermittent faults and prove that the verification of intermittent fault diagnosability can be transformed into the problem of detecting an intermittent fault language. Then, we present a pair verifier constructed by the strict composition of a fault diagnoser and a normal diagnoser, which are the subparts of the diagnoser with respect to the fault events and the normal events, respectively. Finally, we introduce necessary and sufficient conditions for verifying intermittent fault manifestability. [ABSTRACT FROM AUTHOR]

Cyber-physical systems are characterized by the intrinsic combination of software and physical components that usually include (wired and wireless) communication devices, sensors, actuators, and control processing units. Some wireless devices communicate over insecure channels, rendering cyber-physical systems at risk of malicious attacks that might lead to catastrophic damage. This paper touches upon the problem of sensor deception attacks in supervisory control of discrete-event systems, where an attacker can insert, delete, or replace sensor readings to mislead the supervisor and induce system damage. We model potential attacks using nondeterministic finite-state transducers and then introduce a new defence strategy that utilizes insertion functions. Insertion functions are a type of monitoring interface that alters the system's behaviour by adding extra observable events. Finally, we construct a nondeterministic finite-state transducer called a supervisor filter that recovers the original language generated by the plant by handling the altered language. The insertion function and the supervisor filter cooperate to control the system and confuse the intruder without confusing the supervisor. [ABSTRACT FROM AUTHOR]

Sleep and wakefulness are promoted not by a single neural pathway but via wake or sleep-promoting nodes distributed across layers of the brain. We equate each layer with a brain region in proposing a layered subsumption model for arousal based on a computational architecture. Beyond the brainstem the layers include the diencephalon (hypothalamus, thalamus), basal ganglia, and cortex. In light of existing empirical evidence, we propose that each layer have sleep and wake computations driven by similar high-level architecture and processing units. Specifically, an interconnected wake-promoting system is suggested as driving arousal in each brain layer with the processing converging to produce the features of wakefulness. In contrast, sleep-promoting GABAergic neurons largely project to and inhibit wake-promoting neurons. We propose a general pattern of caudal wake-promoting and sleep-promoting neurons having a strong effect on overall behavior. However, while rostral brain layers have less influence on sleep and wake, through descending projections, they can subsume the activity of caudal brain layers to promote arousal. The two models presented in this work will suggest computations for the layering and hierarchy. Through dynamic system theory several hypotheses are introduced for the interaction of controllers and systems that correspond to the different populations of neurons at each layer. The models will be drawn-upon to discuss future experiments to elucidate the structure of the hierarchy that exists among the sleep-arousal architecture.

This paper addresses the scheduling problem for discrete event systems modeled by labeled Petri nets with time and resource constraints where deadlocks are inevitable. For better resource utilization and shorter processing time, a heuristic algorithm is presented for designing a suitable transition sequence that starts from the initial marking to a set of target markings using basis markings. Specially, two reasons exist for deadlocks in the given system. One is resource exhaustion and the other is unreasonable resource allocation. We only focus on the former. First, the set of target markings, i.e., deadlocks caused by resource exhaustion, is identified using the notion of basis markings and resource-exhausted markings. The basis reachability graph instead of the conventional reachability graph is constructed to avoid state space explosion. An integer linear programming problem based on the notion of deadlocks is carried out to distinguish basis markings, where deadlocks can be reached by firing unobservable transitions only. Then, the A-star algorithm is applied to the basis marking space to schedule the transition firing sequences and the optimal results may be obtained. Unpromising searching areas are reduced and only a part of the markings is probed. Finally, a numerical case is studied to verify the effectiveness of the proposed algorithm. The main advantages of the proposed approach include that the exhaustive enumeration of the reachability space can be avoided and the calculation can be completed off-line.

Reinforcement learning (RL) can obtain the supervisory controller for discrete-event systems modeled by finite automata and temporal logic. The published methods often have two limitations. First, a large number of training data are required to learn the RL controller. Second, the RL algorithms do not consider uncontrollable events, which are essential for supervisory control theory (SCT). To address the limitations, we first apply SCT to find the supervisors for the specifications modeled by automata. These supervisors remove illegal training data violating these specifications and hence reduce the exploration space of the RL algorithm. For the remaining specifications modeled by temporal logic, the RL algorithm is applied to search for the optimal control decision within the confined exploration space. Uncontrollable events are considered by the RL algorithm as uncertainties in the plant model. The proposed method can obtain a nonblocking supervisor for all specifications with less learning time than the published methods.

Fault-freeness is one of the necessary guarantees for healthy and stable operations of discrete event systems. Traditional diagnostic models may fail since sensors may suffer electronic component failures, communication failures, or atmospheric electromagnetic interference. Robust diagnosis problem has attracted more and more attention since it improves reliability of the diagnosis technology. When generating the Petri net reachability graph necessary for constructing a reachability diagnoser, one may face the state explosion problem. As a Petri net gets more complicated, the complexity of its reachability graph also increases exponentially. With the basis reachability graph, a lightweight diagnoser named a basis reachability diagnoser is developed, together with a robust basis reachability diagnoser obtained by dilating the basis reachability graph. Compared with reachability graphs, the advantages of basis reachability graphs in construction complexity are confirmed and the efficiency in robust diagnosability analysis is improved.

Roughly speaking, differential privacy is a privacy-preserving strategy that guarantees attackers to be unlikely to infer, from the previous system output, the dataset from which an output is derived. This work introduces differential privacy to discrete event systems modeled by probabilistic automata to protect the state information pertaining to system resource configurations. State differential privacy is defined to protect the initial state of a discrete event system, which represents its initial resource configuration. Step-based state differential privacy verification is proposed in the framework of probabilistic automata, such that an attacker is unlikely to determine the initial state from which a system evolves, within a finite step of observations, if two systems with two different initial states satisfy state differential privacy. Specifically, the probability distributions of generating observations within a finite step from the two different initial states are approximate. If the two systems do not satisfy state differential privacy, a control specification is proposed, such that state differential privacy is enforced via supervisory control that is maximally permissive. Experimental studies are given to illustrate that the proposed method can effectively verify state differential privacy and enforce privacy protection in the probabilistic automata framework. [ABSTRACT FROM AUTHOR]

A new approach to the verification of current-state opacity for discrete event systems is proposed in this paper, which is modeled with unbounded Petri nets. The concept of opacity verification is first extended from bounded Petri nets to unbounded Petri nets. In this model, all transitions and partial places are assumed to be unobservable, i.e., only the number of tokens in the observable places can be measured. In this work, a novel basis coverability graph is constructed by using partial markings and quasi-observable transitions. By this graph, this research finds that an unbounded net system is current-state opaque if, for an arbitrary partial marking, there always exists at least one regular marking in the result of current-state estimation with respect to the partial marking not belonging to the given secret. Finally, a sufficient and necessary condition is proposed for the verification of current-state opacity. A manufacturing system example is presented to illustrate that the concept of current-state opacity can be verified for unbounded net systems. [ABSTRACT FROM AUTHOR]

Scan chain-based Design for Testability is the industry standard in use for testing manufacturing defects in the semiconductor industry to ensure the structural and functional correctness of chips. Fault coverage is significantly enhanced due to the higher observability and controllability of the internal latches. These ensuing benefits to testing, if misused, expose vulnerabilities that can be detrimental to the security aspects, especially in the context of crypto-chips that contain a secret key. Hence, it remains of paramount importance for a chip designer to secure crypto-chips against various scan attacks. A countermeasure is proposed in this article that preserves the secrecy of an embedded key in a cryptographic integrated circuit running an Advanced Encryption Standard (AES) implementation. A novel design involving a hardware unit is illustrated that circumvents differential scan attacks by essentially performing bit flips deterministically, using a precomputed mask value. This helps secure the chip while retaining full testability. The controller logic directly depends on a mask determination algorithm that can defend against any scan attack with O(1) theoretical complexity. Security analysis of our proposed defense procedure is performed in the framework of Discrete Event Systems (DES). The sequential scan circuit of an AES cryptosystem is modeled as a DES using Finite State Automata. A security notion, Opacity, is used to quantify and formally verify the security aspects of our controlled system, which shows that the entropy of the secret key is preserved. A case study is performed that shows to mitigate state-of-the-art differential scan attacks successfully at a nominal extra overhead of 1.78%. [ABSTRACT FROM AUTHOR]

Copyright of Automatisierungstechnik is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Control algorithms for programmable logic controllers are still developed based on the experience of those responsible for control in the industry. The IEC-61131-3 standard considers five programming languages: Ladder Diagram, Structured Text, Function Block Diagram, Instruction List, and Sequential Function Diagram, which use different function blocks to develop control algorithms. Within the control algorithms for discrete event systems, there are two types of blocks: those with discrete inputs and outputs, and those with discrete and analog inputs and discrete output. Of the latter, the present research shows the analysis and formal model of the blocks including the problems of accumulation of tokens and the restoration of the coils. This proposal includes logical blocks of timers, counters, positive and negative transition detectors and bistable elements, which, together with the AND, OR, AND-OR, contact lock, auto-loop and Set-Reset logics, can be modeled and analyzed control algorithms with a greater degree of complexity. This guarantees the safety of workers as well as machines. [ABSTRACT FROM AUTHOR]

In the realm of data protection strategies, differential privacy ensures that unauthorized entities cannot reconstruct original data from system outputs. This study explores discrete event systems, specifically through probabilistic automata. Central is the protection of state data, particularly the initial state privacy of multiple starting states. We introduce an evaluation criterion to safeguard initial states. Using advanced algorithms, the proposed method counters the probabilistic identification of any state within this collection by adversaries from observed data points. The efficacy is confirmed when the probability distributions of data observations tied to these states converge. If a system’s architecture does not meet state differential privacy demands, we propose an enhanced supervisory control mechanism. This control upholds state differential privacy across all initial states, maintaining operational flexibility within the probabilistic automaton framework. Concluding, a numerical analysis validates the approach’s strength in probabilistic automata and discrete event systems.

The problem of robust predictability against sensor attacks is investigated. The objective of a diagnoser is to predict the occurrence of a critical event of a discrete event system (DES) under partial observation. An attacker may rewrite the diagnoser observation by inserting fake events or erasing real events. Two novel structures, namely, real diagnoser and the fake diagnoser, are constructed based on the diagnoser of the system. We compute the hybrid diagnoser as the parallel composition of the real diagnoser and the fake diagnoser. The hybrid diagnoser can be used to verify if a critical event of the system is robustly predictable when an attacker tampers with the diagnoser observation.

This article aims to provide a perspective on the foundations and developments of the net unfolding techniques and their applications to discrete event systems. The numerous methods applied to concurrency presented in the literature can be roughly divided into two classes: those that assume concurrency can be represented by means of a non-deterministic form, and those that represent concurrency by means of causal relations. This study serves as an ideal starting point for researchers interested in true concurrency semantics by offering a concise literature review of one of the major streams of research towards concurrency and interleaving problems. In order to cope with the state-explosion problem, the unfolding approach is used. Based on the findings of concurrency theory, interleaving semantics are replaced with a unique partially ordered occurrence net. In this paper, we aim to provide a comprehensive review on the history of net unfoldings, the methods that are based on these unfoldings, and how they are used in discrete event systems for automatic verification and compact representations purposes. [ABSTRACT FROM AUTHOR]

The boom seen in artificial intelligence in recent years has led to a revolution in the automotive industry. Numerous automakers around the world, such as Tesla, Toyota, Honda, and BMW, have achieved giant strides in the development of e-autonomous vehicles. Consequently, shared electric automated vehicle mobility (SEAVM) systems, which are a crucial part of future innovative transportation solutions, have attracted significant attention from the research community, particularly from a design perspective. However, the flexibility of shared automated mobility systems may lead to a self-operating technology issue (unequal distribution of vehicles), since users in these systems can pick up and drop off electric vehicles wherever they like. With this in mind, this paper addressed the issues of autonomous repositioning and the assignment of shared autonomous electric vehicle systems to balance a system's network and fulfill its demand. Modeling, analysis and assessment of the system's performance were carried out using stochastic Petri nets formalism, which included determining the average time areas were empty/congested and the number of unserved consumers, and estimating the redistribution service launch moment. Furthermore, many simulation scenarios were analyzed, including repositioning and without repositioning scenarios, in order to evaluate the efficiency of the model and to show the potential of using Petri nets as a probabilistic formalism approach for the modeling of e-automated mobility systems. [ABSTRACT FROM AUTHOR]

Given a discrete event system, it is said to be opaque if an intruder who can partially observe system behavior cannot infer that the system is necessarily in a predefined secret. A discrete event system is current-state opaque if an intruder is never able to verify whether the current state of the system is within the secret states. This article addresses the verification of current-state opacity of a discrete event system modeled with Petri nets, where the secret is defined as a set of states. The existing methods cannot deal with large-sized systems due to the curse of dimensionality. Multi-valued decision diagrams (MDDs) are widely accepted as an efficient and compact data structure for representing the extremely large reachability sets of Petri nets. We show that MDDs can be used in Petri nets with partial observable transitions and propose an approach for the verification of current-state opacity for bounded Petri nets. It is shown by experimental studies that the symbolic approach is practically more efficient than traditional techniques such as basis reachability graphs (BRGs). [ABSTRACT FROM AUTHOR]

This paper addresses the fault diagnosis problem of PLC-based systems that can be modeled as Petri nets under a certain level of abstraction. The existing Petri-net-based fault diagnosis approaches often associate transitions and/or places with sensors and require that any change in sensor readings needs to be treated by a PLC, leading to a situation that the PLC would be too busy processing the changes in sensor readings to perform other tasks. This paper assumes that a PLC does not monitor the changes of readings of sensors all the time, but periodically reads the values of sensors when needed. The system output is defined as a marking sequence interleaved with possible observed transitions. A fault diagnosis algorithm is developed by defining and solving integer linear programing (ILP) problems whose size is regardless of the length of the system output. The proposed approach enjoys high computational efficiency compared with other ILP-based approaches and is more suitable for fault diagnosis of PLC-based systems with low computing power. [ABSTRACT FROM AUTHOR]

The paper concerns the design of a framework for implementing fault-tolerant control of hybrid assembly systems that connect human operators and fully automated technical systems. The main difficulty in such systems is related to delays that result from objective factors influencing human operators’ work, e.g., fatigue, experience, etc. As the battery assembly system can be considered a firm real-time one, these delays are treated as faults. The presented approach guarantees real-time compensation of delays, and the fully automated part of the system is responsible for this compensation. The paper begins with a detailed description of a battery assembly system in which two cooperating parts can be distinguished: fully automatic and semi-automatic. The latter, nonderministic in nature, is the main focus of this paper. To describe and analyze the states of the battery assembly system, instead of the most commonly used simulation, the classic max-plus algebra with an extension allowing one to express non-deterministic human operators’ work is used. In order to synchronize tasks and schedule (according to the reference schedule) automated and human operators’ tasks, it is proposed to use a wireless IoT platform called KIS.ME. As a result, it allows a reference model of human performance to be defined using fuzzy logic. Having such a model, predictive delays tolerant planning is proposed. The final part of the paper presents the achieved results, which clearly indicate the potential benefits that can be obtained by combining the wireless KIS.ME architecture (allocated in the semi-automatic part of the system) with wired standard production networks.

This paper investigated the verification of detectability for discrete event systems based on a class of partially observed unbounded Petri nets. In an unbounded net system, all transitions and partial places are assumed to be unobservable. The system administrator can only observe a few observable places, i.e., the number of tokens at these places can be observed, allowing for the estimation of current and subsequent states. The concepts of quasi-observable transitions, truly unobservable transitions, and partial markings are used to construct a basis coverability graph. According to this graph, four sufficient and necessary conditions of detectability are proposed. Correspondingly, a specific example is proposed to prove that the detectability can be verified in the unbounded net system. Furthermore, based on the conclusion of detectability, the system’s ability to detect critical states was explored by using the basis coverability graph, called C-detectability. Two real-world examples are proposed to show that the detectability of discrete event systems has not only pioneered new research methods, but also demonstrated that the real conditions faced by this method are more general, and it has overcome the limitations of relying only on the ideal conditions of bounded systems for verification.

Information security is an important area of concern in modern computer-integrated systems. It involves implementing preventative measures to protect confidential data from potential vulnerabilities, such as unauthorized access, secret disclosure, modification, or destruction. Considering such threats, we investigate a particular confidentiality property called opacity, which specifies a system’s ability to cover its ‘secret’ data from being interfered with by outside observers, termed as intruders. This paper discusses language-based opacity formulation and verification in the context of discrete event systems represented by partially observed Petri nets. In this context, we identify two opacity properties, called consistency and non-secrecy; then, we exploit the mathematical characterization of a net system, to separately check each property, by specifying two feasibility problems. The proposed method is carried out for two distinct settings of a system. The first setting is centralized, where an intruder is granted complete information about the system structure but a partial observation of its behavior. The second setting is decentralized, where a group of intruders cooperates to reveal the secret language, by using a coordinator. Finally, experimental findings are given, to demonstrate the proficiency of the proposed approach.

This paper considers the verification of decentralized fault pattern diagnosability for discrete event systems, where the pattern is modeled as a finite automaton whose accepted language is the objective to be diagnosed. We introduce a notion of codiagnosability to formalize the decentralized fault pattern diagnosability, which requires the pattern to be detected by one of the external local observers within a bounded delay. To this end, a structure, namely a verifier, is proposed to verify the codiagnosability of the system and the fault pattern. By studying an indeterminate cycle of the verifier, sufficient and necessary conditions are provided to test the codiagnosability. It is shown that the proposed method requires polynomial time at most. In addition, we present an approach to extend the proposed verifier structure so that it can be applied to centralized cases.