Practical Model Checking of a Home Area Network System: Case Study

The integrated communication infrastructure is the core of the Smart Grid architecture. Its two-way communication and information flow provides this network with all needed resources in order to control and manage all connected components from the utility to the customer side. This latter, named the Home Area Network or HAN, is a dedicated network connecting smart devices inside the customer home, and using different solutions. In order to avoid problems and anomalies along the process life cycle of developing a new solution for HAN network, the modeling and validation is one of the most powerful tools to achieve this goal. This paper presents a practical case study of such validation. It intends to validate a HAN SDL model, described in a previous work, using model checking techniques. It introduces a method to translate the SDL model to a Promela model using an intermediate format IF. After the generation of the Promela model, verification is performed to ensure that some functional properties are satisfied. The desired properties are defined in Linear Temporal Logic (LTL), and DTSPIN (an extension of SPIN with discrete time) model checker is used to verify the correctness of the model

Liveness and Reachability Analysis of BPMN Process Models

Business processes are usually defined by business experts who require intuitive and informal graphical notations such as BPMN (Business Process Management Notation) for documenting and communicating their organization activities and behavior. However, BPMN has not been provided with a formal semantics, which limits the analysis of BPMN models to using solely informal techniques such as simulation. In order to address this limitation and use formal verification, it is necessary to define a certain “mapping” between BPMN and a formal language such as Concurrent Sequential Processes (CSP) and Petri Nets (PN). This paper proposes a method for the verification of BPMN models by defining formal semantics of BPMN in terms of a mapping to Time Petri Nets (TPN), which are equipped with very efficient analytical techniques. After the translation of BPMN models to TPN, verification is done to ensure that some functional properties are satisfied by the model under investigation, namely liveness and reachability properties. The main advantage of our approach over existing ones is that it takes into account the time components in modeling Business process models. An example is used throughout the paper to illustrate the proposed method

Modèles de chaîne de Markov pour la classification automatique des services

La bande passante des réseaux mobiles est une ressource très rare, par conséquent les opérateurs sont contraints à connaître le plus précisément possible tous les services transportés sur leurs réseaux, afin de mieux surveiller leur usage et optimiser ces ressources. Dans ce papier on propose une méthode de classification automatique de services basée sur les modèles de chaînes de Markov. Cette méthode est basée sur l'aspect fonctionnel des applications et modélise l'ordre de séquence de paquets d'une application par une chaîne de Markov afin d'identifier une "signature" à cette application. La théorie de test d'hypothèses est employée pour tester si une séquence de paquets est produite par le service à détecter ou par un autre service. Nous nous sommes basés sur des traces réelles du réseau d'Orange France pour calibrer les modèles Markovien et évaluer notre méthode

A Multiple LSPs Approach to Secure Data in MPLS Networks

Abstract — MPLS security is an evolving issue which has been raised by many researchers and service providers. The basic architecture of MPLS network does not provide security services such as encryption. Therefore, MPLS does not protect the confidentiality of data transmitted. This paper provides a mechanism to enhance the security in MPLS networks by proposing a modified (k, n) Threshold Secret Sharing scheme where the n shares obtained are send over multiple disjoint paths. We have implemented our approach to measure its time overhead on packet transmission

New approach for efsm-based passive testing of web services

Abstract. Fault management, including fault detection and location, is an important task in management of Web Services. Fault detection can be performed through testing, which can be active or passive. Based on passive observation of interactions between a Web Service and its client, a passive tester tries to detect possible misbehaviors in requests and/or responses. Passive observation is performed in two steps: passive homing and fault detection. In FSM-based observers, the homing consists of state recognition. However, it consists of state recognition and variables initialization in EFSM-based observers. In this paper, we present a novel approach to speed up homing of EFSM-based observers designed for observation of Web Services. Our approach is based on combining observed events and backward walks in the EFSM model to recognize states and appropriately initialize variables. We present different algorithms and illustrate the procedure through an example where faults would not be detected unless backward walks are considered

New approach for EFSM-based passive testing of web services

Fault management, including fault detection and location, is an important task in management of Web Services. Fault detection can be performed through testing, which can be active or passive. Based on passive observation of interactions between a Web Service and its client, a passive tester tries to detect possible misbehaviors in requests and/or responses. Passive observation is performed in two steps: passive homing and fault detection. In FSM-based observers, the homing consists of state recognition. However, it consists of state recognition and variables initialization in EFSM-based observers. In this paper, we present a novel approach to speed up homing of EFSM-based observers designed for observation of Web Services. Our approach is based on combining observed events and backward walks in the EFSM model to recognize states and appropriately initialize variables. We present different algorithms and illustrate the procedure through an example where faults would not be detected unless backward walks are considered