Method for Attack Tree Data Transformation and Import Into IT Risk Analysis Expert Systems

Information technology (IT) security risk analysis preventatively helps organizations in identifying their vulnerable systems or internal controls. Some researchers propose expert systems (ES) as the solution for risk analysis automation since risk analysis by human experts is expensive and timely. By design, ES need a knowledge base, which must be up to date and of high quality. Manual creation of databases is also expensive and cannot ensure stable information renewal. These facts make the knowledge base automation process very important. This paper proposes a novel method of converting attack trees to a format usable by expert systems for utilizing the existing attack tree repositories in facilitating information and IT security risk analysis. The method performs attack tree translation into the Java Expert System Shell (JESS) format, by consistently applying ATTop, a software bridging tool that enables automated analysis of attack trees using a model-driven engineering approach, translating attack trees into the eXtensible Markup Language (XML) format, and using the newly developed ATES (attack trees to expert system) program, performing further XML conversion into JESS compatible format. The detailed method description, along with samples of attack tree conversion and results of conversion experiments on a significant number of attack trees, are presented and discussed. The results demonstrate the high method reliability rate and viability of attack trees as a source for the knowledge bases of expert systems used in the IT security risk analysis process.This article belongs to the Special Issue Human-Centered Computing and Information Security: Recent Advances & Intelligent Application

Information Security Risk Assessment Method for Ship Control System Based on Fuzzy Sets and Attack Trees

Information security risk assessment for industrial control system is usually influenced by uncertain factors. For effectively dealing with problem that the uncertainty and quantification difficulties are caused by subjective and objective factors in the assessment process, an information security risk assessment method based on attack tree model with fuzzy set theory and probability risk assessment technology is proposed, which is applied in a risk scenario of ship control system. Firstly, potential risks of the control system are analyzed and the attack tree model is established. Then triangular fuzzy numbers and expert knowledge are used to determine the factors that influence the probability of a leaf node and the leaf nodes are quantified to obtain the interval probability. Finally, the fuzzy arithmetic is used to determine the interval probability of the root node and the attack path. After defuzzification, the potential risks of the system and the probability of occurrence of each attack path are obtained. Compared with other methods, the proposed method can greatly reduce the impact of subjectivity on the risk assessment of industrial control systems and get more stable, reliable, and scientific evaluation results