Federated Learning (FL) is susceptible to adversarial attacks, such as Label Flipping (LF) and Backdoor, where malicious clients manipulate the updates of their local model to reduce the global model’s performance. Traditional FL relies on a centralised aggregator, which must be trusted, creating a single point of failure. This centralization not only increases computational cost but also introduces scalability challenges. To address these issues, we propose a Blockchain (BC) based FL framework that decentralises the aggregation process and incorporates an enhanced Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method to identify and remove malicious updates without ignoring minor groups. Our approach eliminates the need for a centralised aggregator by leveraging BC’s smart contracts to aggregate the global model. Simultaneously, Enhanced DBSCAN identifies malicious updates in the parameter space, effectively mitigating adversarial influence while preserving privacy. We evaluate both of our framework and the traditional FL under LF red and Backdoor attacks, experimental results demonstrate that our approach outperforms the traditional FL according to multiple metrics, including accuracy, loss, precision, recall, and F1-score. These findings emphasise the effectiveness of our BC-based decentralised aggregation combined with enhanced DBSCAN technique in improving the robustness and security of FL systems.

Generalized stochastic Petri nets (GSPNs) have been extended to several dynamic-structure formalisms providing suitable tools for the modeling and verification of reconfigurable discrete-event systems (R-DESs). However, analyzing the performance of large-complex R-DESs remains a big challenging issue. Indeed, dynamic-structure GSPNs still rely on old-fashioned techniques often causing the state-space explosion problem. In this article, we present a new technique for the quantitative analysis of a dynamic-structure formalism called reconfigurable GSPNs without computing the whole state space. This work describes new reconfiguration forms used to preserve desired quantitative properties of parts of interest after each reconfiguration. Therefore, it is only required to verify the examined properties at an initial configuration. The proposed technique is proven to effectively reduce the state space and shorten the computation time in such cases. Finally, some experimental results are provided to illustrate that, from a computational perspective, the developed approach outperforms the existing tools.

This article deals with improved formal verification of reconfigurable discrete-event systems (DESs) modeled by reconfigurable timed net condition event systems (R-TNCESs). An R-TNCES consists of a set of timed net condition event systems, each of which represents a particular behavior of a DES, and a reconfiguration scenario is a switching mode from a timed net condition event system to another. However, the verification with the classical computation tree logic (CTL) as well as the related extensions increases the number of properties for complete verification of a complex R-TNCES. We propose reconfigurable CTL as a new extension of CTL to reduce such a number. New connectors of reconfigurable CTL are proposed, with their formal syntax and semantics, and a set of new algorithms is proposed to control the complexity of model checking. We use a benchmark production system for the performance evaluation of the proposed approach. Reduction in the number of properties to be checked is shown, and consequently, the related validation time is reduced.Note to Practitioners—This research represents a new orientation for guiding efficiently the model checking of reconfigurable discrete-event systems. A classification of properties described in computation tree logic (CTL), according to their dominance and equivalence relations, allows one to conduct an efficient verification by avoiding inefficient calculation due to redundant properties. In this case, giving a verification order for these properties allows one to shorten their verification time. An extension named reconfigurable CTL describes the new syntax of the proposed classification. This approach can be applied in modeling and verification of advanced reconfigurable systems arising from smart grids, adaptive sensor networks, intelligent transportation, reconfigurable manufacturing, and embedded systems.

This paper deals with the formal verification of reconfigurable discrete event control systems (RDECSs) using reconfigurable timed net condition/event systems (R-TNCESs) formalism. A reconfigurable system switches from a mode to another during its working process to adapt its behavior to the related environment. By including such a feature, RDECSs become complex and their verification is often expensive in terms of computation time and memory. In this paper, a new methodology for formal verification of RDECSs is proposed in order to ensure the correctness of these systems with a reduced cost (decreasing the verification time and memory occupation). The proposed contribution includes an improved modeling and verification of RDECSs. The modeling with R-TNCESs is enriched with all reconfiguration forms, and the verification involves an improvement method that avoids any redundancy and cancels unnecessary calculations. In addition, a visual tool called Rec-AG based on the proposed methodology is developed. The performance evaluation of this paper is achieved by measuring computation time and memory for several systems and different sizes of the problem. This paper's contribution is applied to the benchmark production system FESTO.

This paper deals with reconfigurable discrete event control systems (RDECSs). We model RDECSs using reconfigurable timed net condition/event systems (R-TNCESs) formalism which is an extension from Petri nets to deal with reconfiguration properties. Model-based diagnosis algorithms are widely used in academia and industry to detect faulty components and ensure systems safety. The application of these methods on reconfigurable systems is impossible due to their special behavior. In this paper, we propose accomplishing techniques of backward reachability to make reconfigurable systems model-based diagnosis possible using R-TNCESs. The flexibility among reconfigurable systems like RDECSs allows them to challenge recent requirements of markets. However, such properties and complicated behavior make their verification task being complex and sometimes impossible. We deal with the previous problem by proposing a new methodology based on backward reachability of RDECSs using (R-TNCESs) formalism including improvement methods. The proposed methodology serves to reduce as much as possible redundant computations and gives a package to be used in model-based diagnosis algorithms. The paper’s contribution is applied to a benchmark modular production system. Finally, a performance evaluation is achieved for different sizes of the problem to study benefits and limits of the proposed methodology among large-scale systems.

This paper deals with formal modeling and verification of reconfigurable hierarchical discrete-event control systems (RDECSs). The system's behavior is with a dynamic structure for being adapted to related environment. We propose an extension of timed automata named reconfigurable hierarchical timed automata (RHTA) to consider hierarchy and reconfigurability of the considered system. Since the verification becomes an expensive task in terms of computation time and memory, an improved verification methodology is proposed for RHTA where redundancies and similarities between system's configurations are considered which controls verification cost. The proposed contribution is applied to an example to evaluate the related performance where gains in term of verification time are marked.

To guarantee a better power availability in complex power systems, this paper provides a new strategy that deals with smart grids rebuilding for faults recovery. We propose a heuristic that schedules technical teams interventions and allows to carry favour clients with no recovery sources compared with those that are covered by renewable sources, and the ones recovered by pertinent emergency lines. Thus, we overcome this complexity by providing an oriented cloud architecture based on effective computing sources for assisting technical teams in recovery, it permits to obtain gains in term of total energy availability and to reduce loss time. We implement a simulation tool for smart grid rebuilding based on a cloud system called SGCS-RB which is experimented on different smart grids, and we evaluate the number of recovered failures which is improved thanks to the proposed contribution.

Access control is an important issue in multi-domain information systems. A variety of access control models have been developed to address different aspects of security problems in such systems. Currently, the two most popular models are role-based access control (RBAC) and Attribute-based access control (ABAC). Providing a hybrid model which considers both the “role” concept and the “attributes” has become an important research topic. In this paper, we propose a new access control model based principally on roles, attributes, access modes and the type of resources. This model combines the advantages of the two models RBAC and ABAC and overcomes their limitations.

In Reconfigurable Manufacturing Systems (RMSs), the structure of the system can be changed during execution of the system. This reconfiguration can be motivated by a new requirement in the production process, or to avoid some problems caused by machines breakdowns. These systems offer a high flexibility leading to more productivity and efficiency. However, their design is more complicated implying new techniques and paradigms. The use of formal high level Petri Nets offers the ability to design these systems and to analyse or prove their properties. In this paper, we apply Reconfigurable Object Nets (RONs) for the modelling, simulation and analysis of reconfigurable manufacturing systems. We propose a formal approach, where the reconfiguration is specified as graph transformations, the simulation is realized using the RON-tool, and the analysis exploits some software tools such as TINA-tool and PIPE-tool.

Using Petri nets to model reconfigurable systems, where structure changes during runtime, have been one of the research axes in high level Petri nets domain. Numerous formalisms with different particularities have been proposed. These formalisms try to deal with some aspects of these systems. In the present paper, we propose a new PNets-based formalism “Flexible Nets” that we consider more general and more adequate to model reconfigurable systems. The current formalism allows to the net to be flexible and its structure can be changed with few constraints. Places, transitions, and arcs can be added and deleted from the net during its execution. These qualities will offer to the developer a sophisticated tool to model easily his system. We present the formal definition of the formalism, a case study on a real and complex system, and then we will discuss some analysis and verification issues.

Summary form only given. This paper proposes a modeling approach easy to master in practice and from which one could directly derive a formal model capturing the main features of the dynamic interactions involved in multiagent systems (MAS). This approach follows two steps. The first consists to describe agent interactions in a MAS using Agent Unifying Model Language (AUML). The second step consists in translating this AUML description into a recursive colored Petri net (RCPN) model by following suitable rules. The choice of the RCPN formalism is motivated by its ability to model the dynamic agent planning ensuring the interleaving between planning and execution of complex actions and the availability of formal analysis and verification methods and tools.