AttackTree, through the use of attack tree models, allows the user to model the probability that different attacks will succeed. AttackTree also allows users to define indicators that quantify the cost of an attack, the operational difficulty in mounting the attack and any other relevant quantifiable measure that may be of interest. Questions such as ‘which attacks have the highest probability of success at a low cost to the attacker?’ or ‘which attacks have the highest probability of success with no special equipment required?’ can be answered using AttackTree. In AttackTree, different categories and levels of consequence may also be assigned to nodes in the attack tree. A successful attack may have financial, political, operational and safety consequences. A partially successful attack may have a different level of consequence to a totally successful attack. All these types of consequence measure may be modeled in AttackTree.
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References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Hong, Jin B.; Kim, Dong Seong; Chung, Chun-Jen; Huang, Dijiang: A survey on the usability and practical applications of graphical security models (2017)
- Kordy, Barbara; Piètre-Cambacédès, Ludovic; Schweitzer, Patrick: DAG-based attack and defense modeling: don’t miss the forest for the attack trees (2014)