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Project Team

Prof. Ana Fred Hugo Gamboa


This project presents a new soft biometric trait for remote user authentication using a conventional web browser. We developed a system that captures the user interaction via a pointing device, and uses associated behavioural information to verify the identity of an individual. Exploring statistical pattern recognition techniques, we found that the normal user interaction with the computer entails discriminant information, useful for creating a behavioural biometric human authentication system.

WebBiometrics – User verification via Web Interaction

We introduce a biometric trait based on user behavior extracted from the human interaction with a web page via a pointing device. We propose the integration of this soft biometric trait in a conventional login Internet page to enhance the security of informatics systems. We call this security layer WebBiometrics. This layer monitors the user’s mouse movements while he clicks his PIN code numbers. The proposed biometric method provides a non-intrusive soft behavioral biometric add-on to enhance on-line security.

System architecture

The WebBiometric system is based on a client-server architecture implemented over the Internet. The user accesses a web-page on his computer (client) that transmits information to the remote authentication system (server). The system is composed by the following building blocks: (a) acquisition module (b) feature extraction; (c) feature selection; (d) parametric learning; and (e)þ statistical sequential classifier.

Data Acquisition

We collected data from 50 volunteering subjects (engineering students) while using the system, interacting with a web page, with the same structure of the diagram in the figure at the top, during about 10-15 minutes. This way, we created a repository of approximately 5 hours of interaction.


The best results were obtained by exploring a user tuned feature selection approach and a sequential classifier that uses several strokes (mouse movements between consecutive clicks) from the user. In the figure on the right we can see the effect of the interaction time on the EER. Increasing interaction times lead to decreasing error rates in user identification.
The table on the right compares some other behavioral biometric techniques with the proposed mouse movement biometric with different strokes length durations. Given the performance of the proposed biometric technique, there are some situations, like continuous biometric applications, that the performance is comparable to the other popular behavioural biometrics techniques, with the advantages of low intrusion, no need for special sensors, and the capability of being remotelly colected. We also consider this trait usefull for integration on multibiometrics systems.


Hugo Gamboa and Vasco Ferreira, Widam - web interaction display and monitoring. 5th International Conference on Enterprise Information Systems, ICEIS 2003, Angers, France, 2003.

Hugo Gamboa and Ana Fred, A behavioral biometric system based on human-computer interaction, Proceedings of SPIE Vol. 5404, p. 381-392, Biometric Technology for Human Identification; Anil K. Jain, Nalini K. Ratha; Eds. Orlando USA, 2004.

Hugo Gamboa, Ana Fred and António Alves Vieira, Prevention or Identification of Web Intrusion via Human Computer Interaction Behaviour - A Proposal, Meeting Prooceedings of Nato Research and Technology Organization Symposium on Systems, Concepts and Integration (SCI) Methods and Technologies for Defence Against Terrorism, RTO-MP-SCI-158, London, United Kingdom, 2004.

Hugo Gamboa, Ana Fred and Anil K.Jain, Webbiometrics: User Verification Via Web Interaction,. Biometric Symposium, BCC, Baltimore, USA, 2007 (Finalist of the EBF European Biometrics Research Award 2007, the work having been presented on October 3, Brussels, Belgium).






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