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Modeling cyber conflicts using an extended Petri Net formalism

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2 Author(s)
Zakrzewska, A.N. ; Cyberspace Sci. & Inf. Intell. Res. Group, Oak Ridge Nat. Lab., Oak Ridge, TN, USA ; Ferragut, E.M.

When threatened by automated attacks, critical systems that require human-controlled responses have difficulty making optimal responses and adapting protections in real-time and may therefore be overwhelmed. Consequently, experts have called for the development of automatic real-time reaction capabilities. However, a technical gap exists in the modeling and analysis of cyber conflicts to automatically understand the repercussions of responses. There is a need for modeling cyber assets that accounts for concurrent behavior, incomplete information, and payoff functions. Furthermore, we address this need by extending the Petri net formalism to allow real-time cyber conflicts to be modeled in a way that is expressive and concise. This formalism includes transitions controlled by players as well as firing rates attached to transitions. This allows us to model both player actions and factors that are beyond the control of players in real-time. We show that our formalism is able to represent situational awareness, concurrent actions, incomplete information and objective functions. These factors make it well-suited to modeling cyber conflicts in a way that allows for useful analysis. MITRE has compiled the Common Attack Pattern Enumeration and Classification (CAPEC), an extensive list of cyber attacks at various levels of abstraction. CAPEC includes factors such as attack prerequisites, possible countermeasures, and attack goals. These elements are vital to understanding cyber attacks and to generating the corresponding real-time responses. We demonstrate that the formalism can be used to extract precise models of cyber attacks from CAPEC. Several case studies show that our Petri net formalism is more expressive than other models, such as attack graphs, for modeling cyber conflicts and that it is amenable to exploring cyber strategies.

Published in:
Computational Intelligence in Cyber Security (CICS), 2011 IEEE Symposium on

Date of Conference: 11-15 April 2011

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