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This paper describes literature works in intrusion detection field. After that, we propose an intrusion detection method in Linux/Unix commands using supervisor synthesis. This method was applied to distinct normal user behavior from intruders behavior. The main features of this work are twofold. It exploits supervisor synthesis in the intrusion detection field. It presents our approach by behavior specification. Two advantages characterize our proposed algorithm for detection. The first advantage is that the algorithm result is a structure. The second advantage is the way of searching faults or intrusions.

In this paper, we focus on the online diagnosis of Automated Production Systems (APS) equipped with sensors and actuators emitting binary signals. These systems can be considered as Discrete Event Systems (DES). The paper presents a Case-Based Reasoning for the Online Diagnosis of All types of Faults in APS (CBR-ODAF). It is an improvement of our approach presented previously in order to remedy its limitations. Firstly, it proposes a new case representation format that describes all the faults to diagnose, adapts to the dynamic aspect of APS, is quite expressive and is easy to understand by human operators. Secondly, it allows to classify in real time each new observation as a ’normal case’, ’faulty case’ or ’unidentified case’ based on a new dissimilarity index which is not intrinsic to the numerical type. It is an index that adapts to our proposed case representation format and describes the degree of difference between cases represented by data of different types (i.e. quantitative and qualitative).