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Creating Evolving User Behavior Profiles Automatically
May 2012 (vol. 24 no. 5)
pp. 854-867
Jose Antonio Iglesias, Carlos III University of Madrid, Madrid
Plamen Angelov, Lancaster University, Lancaster
Agapito Ledezma, Carlos III University of Madrid, Madrid
Araceli Sanchis, Carlos III University of Madrid, Madrid
Knowledge about computer users is very beneficial for assisting them, predicting their future actions or detecting masqueraders. In this paper, a new approach for creating and recognizing automatically the behavior profile of a computer user is presented. In this case, a computer user behavior is represented as the sequence of the commands she/he types during her/his work. This sequence is transformed into a distribution of relevant subsequences of commands in order to find out a profile that defines its behavior. Also, because a user profile is not necessarily fixed but rather it evolves/changes, we propose an evolving method to keep up to date the created profiles using an Evolving Systems approach. In this paper, we combine the evolving classifier with a trie-based user profiling to obtain a powerful self-learning online scheme. We also develop further the recursive formula of the potential of a data point to become a cluster center using cosine distance, which is provided in the Appendix. The novel approach proposed in this paper can be applicable to any problem of dynamic/evolving user behavior modeling where it can be represented as a sequence of actions or events. It has been evaluated on several real data streams.

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Index Terms:
Evolving fuzzy systems, fuzzy-rule-based (FRB) classifiers, user modeling.
Citation:
Jose Antonio Iglesias, Plamen Angelov, Agapito Ledezma, Araceli Sanchis, "Creating Evolving User Behavior Profiles Automatically," IEEE Transactions on Knowledge and Data Engineering, vol. 24, no. 5, pp. 854-867, May 2012, doi:10.1109/TKDE.2011.17
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