International Conference on Dependability of Computer Systems 

About: International Conference on Dependability of Computer Systems is an academic conference. The conference publishes majorly in the area(s): Dependability & Software system. Over the lifetime, 192 publications have been published by the conference receiving 1613 citations.

Normalization as a Preprocessing Engine for Data Mining and the Approach of Preference Matrix

Abstract: This study is emphasized on different types of normalization. Each of which was tested against the ID3 methodology using the HSV data set. Number of leaf nodes, accuracy, and tree growing time are three factors that were taken into account. Comparisons between different learning methods were accomplished as they were applied to each normalization method. A simple matrix was designed to check for the best normalization method based on the factors and their priorities. Recommendations were concluded.

An Artificial Immune System Approach for Fault Prediction in Object-Oriented Software

Abstract: The features of real-time dependable systems are availability, reliability, safety and security. In the near future, real-time systems will be able to adapt themselves according to the specific requirements and real-time dependability assessment technique will be able to classify modules as faulty or fault-free. Software fault prediction models help us in order to develop dependable software and they are commonly applied prior to system testing. In this study, we examine Chidamber-Kemerer (CK) metrics and some method-level metrics for our model which is based on artificial immune recognition system (AIRS) algorithm. The dataset is a part of NASA Metrics Data Program and class-level metrics are from PROMISE repository. Instead of validating individual metrics, our mission is to improve the prediction performance of our model. The experiments indicate that the combination of CK and the lines of code metrics provide the best prediction results for our fault prediction model. The consequence of this study suggests that class-level data should be used rather than method-level data to construct relatively better fault prediction models. Furthermore, this model can constitute a part of real-time dependability assessment technique for the future.

Security Aspects of SCADA and Corporate Network Interconnection: An Overview

Abstract: SCADA (Supervisory Control and Data Acquisition) systems play an important role in industrial process. In the past, these used to be stand-alone models, with closed architecture, proprietary protocols and no external connectivity. Nowadays, SCADA rely on wide connectivity and open systems and are connected to corporate intranets and to the Internet for improve efficiency and productivity. SCADA networks connected to corporate networks brought some new seecurity related challenges. This paper presents an overview of the security aspects of this interconnection.

Formal Semantics and Reasoning about UML Class Diagram

Abstract: The main way of coping with the complexity of software systems is to construct and use models expressed in UML. Unfortunately, the semantics (meaning) of models written in UML is not precisely defined. It may result in the incorrect interpretation of a model and make it hard to strictly verify a model and its transformation. In this paper we formally (mathematically) define UML class diagram and its semantics. The problem of consistency of the diagram is then introduced and some examples of inconsistencies are forwarded.

Distributed Intrusion Detection Framework based on Autonomous and Mobile Agents

Abstract: Implementation of intrusion detection systems with agent technology is one of the new paradigms for intrusion detection for computer systems. In this paper, we propose a distributed intrusion detection framework based on autonomous and mobile agents. In this framework, the mobile agent platform "aglets" is utilized. The system has five types of agents: administrator agents, analyzer agents, connection agents, crisis agents, and update behavior agents. These agents interact with each other to perform the detection task. We also discuss the implementation issues about our system.