Correctness of services and their composition

We study correctness of services and their composition and investigate how the design of correct service compositions can be systematically supported. We thereby focus on the communication protocol of the service and approach these questions using formal methods and make contributions to three scenarios of SOC.Wir studieren die Korrektheit von Services und Servicekompositionen und untersuchen, wie der Entwurf von korrekten Servicekompositionen systematisch unterstützt werden kann. Wir legen dabei den Fokus auf das Kommunikationsprotokoll der Services. Mithilfe von formalen Methoden tragen wir zu drei Szenarien von SOC bei

Distributed synchronous diagnosis of discrete-event systems

Recently, the centralized and decentralized synchronous diagnosis of discreteevent systems have been proposed in the literature. In this work, we propose a di erent synchronous diagnosis strategy called distributed synchronous diagnosis. In this scheme, local diagnosers are computed based on the observation of the fault-free behavior models of the system components. It is considered that these local diagnosers are separated into networks, and are capable of communicating the occurrence of events and their current state estimate to other local diagnosers that belong to the same network. The diagnosers are implemented considering an speci c communication protocol that re nes the state estimate of the faultfree behavior of the system modules, reducing, therefore, the augmented fault-free language considered for synchronous diagnosis. In order to do so, boolean conditions are added to the transitions of the fault-free component models, which check if the occurrence of an observable event is possible according to the current state estimate of other local diagnosers. This leads to the notion of distributed synchronous diagnosability. An algorithm to verify the distributed synchronous diagnosability with polynomial complexity in the state-space of the system component models is proposed.Recentemente, o diagnóstico síncrono centralizado e descentralizado de sistemas a eventos discretos foi proposto na literatura. Neste trabalho, propomos uma estratégia de diagnóstico síncrono diferente, denominada diagnóstico síncrono distribuído. Neste esquema, diagnosticadores locais são construídos com base na observação do comportamento livre de falha dos componentes do sistema. Considera-se que esses diagnosticadores locais são agrupados em redes de comunicação e capazes de informar a ocorrência de eventos e sua estimativa de estado atual a outros diagnosticadores locais pertencentes à mesma rede. Os diagnosticadores são implementados considerando um protocolo de comunicação específico, o qual refina a estimativa de estado do comportamento livre de falha dos módulos do sistema, reduzindo, portanto, a linguagem aumentada livre de falha considerada no diagnóstico síncrono. Isso é feito com a adição de condições booleanas para a transposição de transições dos modelos livre de falha dos componentes do sistema, as quais verificam se a ocorrência de um evento observável é possível de acordo com a estimativa do estado atual dos outros diagnosticadores locais. Isso leva à noção de diagnosticabilidade síncrona distribuída. Um algoritmo para verificar a diagnosticabilidade síncrona distribuída com complexidade polinomial no espaço de estados dos modelos dos componentes do sistema é proposto

Correctness of services and their composition

We study correctness of services and their composition and investigate how the design of correct service compositions can be systematically supported. We thereby focus on the communication protocol of the service and approach these questions using formal methods and make contributions to three scenarios of SOC.Wir studieren die Korrektheit von Services und Servicekompositionen und untersuchen, wie der Entwurf von korrekten Servicekompositionen systematisch unterstützt werden kann. Wir legen dabei den Fokus auf das Kommunikationsprotokoll der Services. Mithilfe von formalen Methoden tragen wir zu drei Szenarien von SOC bei

A Case Study on Formal Verification of Self-Adaptive Behaviors in a Decentralized System

Self-adaptation is a promising approach to manage the complexity of modern software systems. A self-adaptive system is able to adapt autonomously to internal dynamics and changing conditions in the environment to achieve particular quality goals. Our particular interest is in decentralized self-adaptive systems, in which central control of adaptation is not an option. One important challenge in self-adaptive systems, in particular those with decentralized control of adaptation, is to provide guarantees about the intended runtime qualities. In this paper, we present a case study in which we use model checking to verify behavioral properties of a decentralized self-adaptive system. Concretely, we contribute with a formalized architecture model of a decentralized traffic monitoring system and prove a number of self-adaptation properties for flexibility and robustness. To model the main processes in the system we use timed automata, and for the specification of the required properties we use timed computation tree logic. We use the Uppaal tool to specify the system and verify the flexibility and robustness properties.Comment: In Proceedings FOCLASA 2012, arXiv:1208.432

BIOLOGICAL INSPIRED INTRUSION PREVENTION AND SELF-HEALING SYSTEM FOR CRITICAL SERVICES NETWORK

With the explosive development of the critical services network systems and Internet, the need for networks security systems have become even critical with the enlargement of information technology in everyday life. Intrusion Prevention System (IPS) provides an in-line mechanism focus on identifying and blocking malicious network activity in real time. This thesis presents new intrusion prevention and self-healing system (SH) for critical services network security. The design features of the proposed system are inspired by the human immune system, integrated with pattern recognition nonlinear classification algorithm and machine learning. Firstly, the current intrusions preventions systems, biological innate and adaptive immune systems, autonomic computing and self-healing mechanisms are studied and analyzed. The importance of intrusion prevention system recommends that artificial immune systems (AIS) should incorporate abstraction models from innate, adaptive immune system, pattern recognition, machine learning and self-healing mechanisms to present autonomous IPS system with fast and high accurate detection and prevention performance and survivability for critical services network system. Secondly, specification language, system design, mathematical and computational models for IPS and SH system are established, which are based upon nonlinear classification, prevention predictability trust, analysis, self-adaptation and self-healing algorithms. Finally, the validation of the system carried out by simulation tests, measuring, benchmarking and comparative studies. New benchmarking metrics for detection capabilities, prevention predictability trust and self-healing reliability are introduced as contributions for the IPS and SH system measuring and validation. Using the software system, design theories, AIS features, new nonlinear classification algorithm, and self-healing system show how the use of presented systems can ensure safety for critical services networks and heal the damage caused by intrusion. This autonomous system improves the performance of the current intrusion prevention system and carries on system continuity by using self-healing mechanism

A CPN-Approach for DistributedAbductive Reasoning : Application to Causal Model-Based Diagnosis

This thesis deals with fault diagnosis of distributed systems from a model-based view where Coloured Petri Nets are used to describe the systembehaviour. The systems concerned here are those comprising different interactingsubsystems. Coloured Behavioural Petri Nets are defined as a particular CPNintended for the description of a system’s causal behaviour, where each transitionis labelled with a matrix describing explicitly its firing ways. The use of suchmatrices helps in tackling the problem of complexity during backward analysis,and gives rise to a very specific technique based on reachability of CBPNs calledCW-analysis. CBPNs together with the CW-analysis are used to develop a dis-tributed model-based diagnosis approach. The diagnostic system is defined as setof diagnostic agents where each is assigned to diagnose a subsystem. Accordingly,the system model consists of a set of place-bordered CBPNs, whereas CW-analysisis exploited to implement a local diagnosis scheme. Once local diagnoses are ob-tained by the different agents, a cooperation process should be initiated to ensureglobal consistency of such diagnoses