University of Twente Student Theses


Privacy-preserving social DNA-based recommender

Carvajal Gallardo, I. R. (2015) Privacy-preserving social DNA-based recommender.

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Abstract:This research studies current privacy-preserving and familiarity-based recommender systems and introduces a new recommender system based on these existing techniques that uses DNA-similarity between users of the system as a basis for generating recommendations. Techniques for privacy-preserving DNA-matching are researched and incorporated in the setting of a privacy-preserving recommender system. Somewhat homomorphic encryption is used as the standard encryption for both the privacy-preserving DNA-matching and the recommendation generation. The system is first devised in a semi-honest security model and is then extended to the malicious user model. The recommender system is implemented in both security models and its performance is compared to existing privacy-preserving recommender systems.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Computer Science MSc (60300)
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