Date of Graduation


Document Type

Problem/Project Report

Degree Type



Statler College of Engineering and Mineral Resources


Lane Department of Computer Science and Electrical Engineering

Committee Chair

Bojan Cukic

Committee Co-Chair

John Atkins

Committee Member

John Atkins

Committee Member

Cindy Tanner


The progress of technology and the development of powerful databases have made it possible to store and easily access continually increasing amounts of sensitive data about people. Since personal information is becoming common in many different databases, it is vital that this data be hidden to ensure privacy of the individuals whose records are stored in these repositories. Database anonymization is the key to securing these databases by ensuring that database users will be unable to reveal sensitive personal information by intelligently structuring their queries.

We analyzed the structure of the BiomData database which contains images and sound recordings of six biometric modalities acquired from hundreds of volunteers. To ensure the confidentiality of these volunteers, our goal was to prevent queries which would allow database users to obtain images of easily identifiable biometric data (facial images, for example) together with the corresponding images of modalities for which user's anonymity is required (fingerprint images, for example). ERUCES Tricryption® Engine was used to anonymize the links between the six biometric modality tables contained in the database, thereby enhancing privacy of volunteers who participate in the biometric collection study while promoting an open data sharing research environment.