An Enhanced Middleware for Collaborative Privacy in IPTV Recommender Services
Ahmed M. Elmisery, Dmitri Botvich

TL;DR
This paper presents EMCP, a privacy-preserving middleware for IPTV recommender systems that uses trust-based obfuscation and secure computation to protect user preferences while maintaining recommendation accuracy.
Contribution
It introduces a two-stage concealment process with trust-based obfuscation levels and secure multiparty computation for privacy in IPTV recommendations.
Findings
Privacy is effectively protected with minimal impact on recommendation accuracy.
Trust-based obfuscation levels improve privacy control for users.
The framework is validated through IPTV network experiments.
Abstract
One of the concerns users have to confronted when using IPTV system is the information overload that makes it difficult for them to find a suitable content according to their personal preferences. Recommendation service is one of the most widely adopted technologies for alleviating this problem, these services intend to provide people with referrals of items they will appreciate based on their preferences. IPTV users must ensure their sensitive preferences collected by any recommendation service are properly secured. In this work, we introduce a framework for private recommender service based on Enhanced Middleware for Collaborative Privacy (EMCP). EMCP executes a two-stage concealment process that gives the user a complete control on the privacy level of his/her profile. We utilize trust mechanism to augment the accuracy and privacy of the recommendations. Trust heuristic spot users…
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Taxonomy
TopicsPrivacy-Preserving Technologies in Data · Cryptography and Data Security · Privacy, Security, and Data Protection
