A learning-based approach to reactive security
Barth, Adam, Rubinstein, Benjamin I.P., Sundararajan, Mukund, Mitchell, John C., Song, Dawn, & Bartlett, Peter L. (2010) A learning-based approach to reactive security. Financial Cryptography and Data Security, 6052, pp. 192-206.
Despite the conventional wisdom that proactive security is superior to reactive security, we show that reactive security can be competitive with proactive security as long as the reactive defender learns from past attacks instead of myopically overreacting to the last attack. Our game-theoretic model follows common practice in the security literature by making worst-case assumptions about the attacker: we grant the attacker complete knowledge of the defender’s strategy and do not require the attacker to act rationally. In this model, we bound the competitive ratio between a reactive defense algorithm (which is inspired by online learning theory) and the best fixed proactive defense. Additionally, we show that, unlike proactive defenses, this reactive strategy is robust to a lack of information about the attacker’s incentives and knowledge.
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|Item Type:||Journal Article|
|Additional Information:||14th International Conference, FC 2010, Tenerife, Canary Islands, January 25-28, 2010, Revised Selected Papers|
|Keywords:||reactive security, proactive security, game-theoretic model|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > DATA FORMAT (080400)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
Past > Schools > Mathematical Sciences
|Copyright Owner:||Copyright 2010 IFCA/Springer-Verlag|
|Deposited On:||18 Aug 2011 11:50|
|Last Modified:||01 Mar 2012 00:34|
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