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An Enhanced Privacy-Preserving Recommender System

  • Pranav VermaEmail author
  • Harshul Vaishnav
  • Anish Mathuria
  • Sourish Dasgupta
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 939)

Abstract

A recommender system stores historical data collected over a long period from various users, these are used to predict how new and existing users would rate an item. As user data is stored by the system, this poses threat to user’s privacy. The goal of a privacy preserving recommender system is to hide user ratings from system and yet allow to make recommendations.

A recent example is the privacy-preserving recommender scheme proposed by Badsha, Yi and Khalil. Their scheme assumes that the server is semi-honest. However, when the server is malicious an attack is possible, as shown by Mu, Shao and Miglani. In this paper, we propose a simple modification to their scheme, which preserves the privacy of ratings against a malicious server. We demonstrate that the computation and communication costs of modified protocol are reasonable in comparison to original protocol.

Keywords

Recommender system Privacy Collaborative Filtering Content Based Filtering Homomorphic encryption 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Pranav Verma
    • 1
    Email author
  • Harshul Vaishnav
    • 1
  • Anish Mathuria
    • 1
  • Sourish Dasgupta
    • 1
  1. 1.Dhirubhai Ambani Institute of Information and Communication TechnologyGandhinagarIndia

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