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Lane, T. and Brodley, C.E. (1997) Sequence Matching and Learning in Anomaly Detection for Computer Security. Proceedings of the AAAI Workshop on AI Approaches to Fraud Detection and Risk Management, AAAI Press, 43-49.

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• TITLE: Illegal Access Detection in the Cloud Computing Environment

  AUTHORS: Rasim Alguliev, Fargana Abdullaeva

  KEYWORDS: Cloud Computing; Masquerade Attack; Cloud Model; User Similarity; Collaborative Filtering

  JOURNAL NAME: Journal of Information Security, Vol.5 No.2, April 18, 2014

  ABSTRACT: In this paper detection method for the illegal access to the cloud infrastructure is proposed. Detection process is based on the collaborative filtering algorithm constructed on the cloud model. Here, first of all, the normal behavior of the user is formed in the shape of a cloud model, then these models are compared with each other by using the cosine similarity method and by applying the collaborative filtering method the deviations from the normal behavior are evaluated. If the deviation value is above than the threshold, the user who gained access to the system is evaluated as illegal, otherwise he is evaluated as a real user.