Coordination and concurrency aware likelihood assessment of simultaneous attacks
L Samarji, N Cuppens-Boulahia, F Cuppens… - … Conference on Security …, 2015 - Springer
International Conference on Security and Privacy in Communication Networks …, 2015•Springer
To avoid improper responses against attacks, current systems rely on Attack Likelihood
metric. Referring to NIST, Attack Likelihood considers: the attack's complexity, the attackers'
motivation, and potential responses. Previous work on Likelihood assessment are limited to
individual attacks, missing thereby coordination and concurrency aspects between
attackers. Moreover, they do not fulfill all NIST factors. Hence, we propose in this paper a
new framework to properly assess the Likelihood of Individual, Coordinated, and Concurrent …
metric. Referring to NIST, Attack Likelihood considers: the attack's complexity, the attackers'
motivation, and potential responses. Previous work on Likelihood assessment are limited to
individual attacks, missing thereby coordination and concurrency aspects between
attackers. Moreover, they do not fulfill all NIST factors. Hence, we propose in this paper a
new framework to properly assess the Likelihood of Individual, Coordinated, and Concurrent …
Abstract
To avoid improper responses against attacks, current systems rely on Attack Likelihood metric. Referring to NIST, Attack Likelihood considers: the attack’s complexity, the attackers’ motivation, and potential responses. Previous work on Likelihood assessment are limited to individual attacks, missing thereby coordination and concurrency aspects between attackers. Moreover, they do not fulfill all NIST factors. Hence, we propose in this paper a new framework to properly assess the Likelihood of Individual, Coordinated, and Concurrent Attack Scenarios (LICCAS). We are first based on a coordination aware-Game Theoric approach to derive an Attack Likelihood equation. Then, we propose an algorithm to assess the Scenario Likelihood of each attack scenario, considering the concurrency between attackers. We finally experiment LICCAS on a VoIP use case to demonstrate its relevance.
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