USim: A User Behavior Simulation Framework for Training and Testing IDSes in GUI Based Systems
ANSS '06 Proceedings of the 39th annual Symposium on Simulation
Strategy-based behavioural biometrics: a novel approach to automated identification
International Journal of Computer Applications in Technology
Towards building a masquerade detection method based on user file system navigation
MICAI'11 Proceedings of the 10th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
Episode based masquerade detection
ICISS'05 Proceedings of the First international conference on Information Systems Security
Masquerade attacks based on user's profile
Journal of Systems and Software
Expert Systems with Applications: An International Journal
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One of the biggest obstacles faced by user command based anomaly detection techniques is the paucity of data. Gathering command data is a slow process often spanning months or years. In this paper, we propose an approach for data generation based on customizable templates, where each template represents a particular user profile. These templates can either be user-defined or created from known data sets. We have developed an automated tool called RACOON, which rapidly generates large amounts of user command data from a given template. We demonstrate that our technique can produce realistic data by showing that it passes several statistical similarity tests with real data. Our approach offers significant advantages over passive data collection in terms of being non-intrusive and enabling rapid generation of site-specific data. Finally, we report the benchmark results of some well-known algorithms against an original data set and a generated data set.