Abstract
There are several methods to assess the capability of a organization to prevent attacks in a potentially wrong collaborative scenario.
In this paper we explore a methodology based on considering some probabilistic information. We assume that we are provided with a probabilistic user model. This is a model denoting the probability that the entity interacting with the system takes each available choice.
We show how to build these models using the log files. Moreover, we define the meaning of a good, a bad and a suspicious behavior. Finally, we present a mechanism to share the information presented in each node of the collaborative system.
Research partially supported by the Spanish MCYT project TESIS (TIN2009-14312-C02-01).
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Andrés, C., Núñez, A., Núñez, M. (2012). Preventing Attacks by Classifying User Models in a Collaborative Scenario. In: Nguyen, NT., Hoang, K., Jȩdrzejowicz, P. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2012. Lecture Notes in Computer Science(), vol 7653. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34630-9_52
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DOI: https://doi.org/10.1007/978-3-642-34630-9_52
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