4 research outputs found

    Towards Synthesis of Attack Trees for Supporting Computer-Aided Risk Analysis

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    International audienceAttack trees are widely used in the fields of defense for the analysis of risks (or threats) against electronics systems, computer control systems or physical systems. Based on the analysis of attack trees, practitioners can define actions to engage in order to reduce or annihilate risks. A major barrier to support computer-aided risk analysis is that attack trees can become largely complex and thus hard to specify. This paper is a first step towards a methodology, formal foundations as well as automated techniques to synthesize attack trees from a high-level description of a system. Attacks are expressed as a succession of elementary actions and high-level actions can be used to abstract and organize attacks into exploitable attack trees. We describe our tooling support and identify open challenges for supporting the analysis of risks

    Symbolic Model-Checking using ITS-tools

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    International audienceWe present the symbolic model-checking toolset ITS-tools. The model-checking back-end engine is based on hierarchical set decision diagrams (SDD) and supports reachability, CTL and LTL model-checking, using both classical and original algorithms. As front-end input language, we promote a Guarded Action Language (GAL), a simple yet expressive language for concurrency. Transformations from popular formalisms into GAL are provided enabling fully symbolic model-checking of third party (Uppaal, Spin, Divine...) specifications. The tool design allows to easily build your own transformation, leveraging tools from the meta-modeling community. The ITS-tools additionally come with a user friendly GUI embedded in Eclipse

    Formal Template-Based Generation of Attack–Defence Trees for Automated Security Analysis

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    Systems that integrate cyber and physical aspects to create cyber-physical systems (CPS) are becoming increasingly complex, but demonstrating the security of CPS is hard and security is frequently compromised. These compromises can lead to safety failures, putting lives at risk. Attack Defense Trees with sequential conjunction (ADS) are an approach to identifying attacks on a system and identifying the interaction between attacks and the defenses that are present within the CPS. We present a semantic model for ADS and propose a methodology for generating ADS automatically. The methodology takes as input a CPS system model and a library of templates of attacks and defenses. We demonstrate and validate the effectiveness of the ADS generation methodology using an example from the automotive domain

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

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    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
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