Privacy-preserving distributed collaborative filtering
نویسندگان
چکیده
منابع مشابه
Privacy-Preserving Collaborative Filtering
Collaborative filtering (CF) techniques are becoming very popular on the Internet and are widely used in several domains to cope with information overload. E-commerce sites use filtering systems to recommend products to customers based on the preferences of like-minded customers, but their systems do not protect user privacy. Because users concerned about privacy may give false information, it ...
متن کاملShilling Attacks against Privacy-Preserving Collaborative Filtering
Although collaborative filtering with privacy schemes protect individual user privacy while still providing accurate recommendations, they might be subject to shilling attacks like traditional schemes without privacy. There are various studies focusing on either proposing privacypreserving collaborative filtering schemes or developing robust recommendation algorithms against shilling attacks. H...
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This article proposes a new technique for Privacy Preserving Collaborative Filtering (PPCF) based on microaggregation, which provides accurate recommendations estimated from perturbed data whilst guaranteeing user k-anonymity. The experimental results presented in this article show the effectiveness of the proposed technique in protecting users’ privacy without compromising the quality of the r...
متن کاملExamining Users' Attitude towards Privacy Preserving Collaborative Filtering
Privacy hazard to Web-based information services represents an important obstacle to the growth and diffusion of the personalized services. Data obfuscation methods were proposed for enhancing the users’ privacy in recommender systems based on collaborative filtering. Data obfuscation can provide statistically measurable privacy gains. However, these are measured using metrics that may not be n...
متن کاملPrivacy Preserving Collaborative Filtering from Asymmetric Randomized Encoding
Collaborative filtering is a famous technique in recommendation systems. Yet, it requires the users to reveal their preferences, which has undesirable privacy implications. Over the years, researchers have proposed many privacy-preserving collaborative filtering (PPCF) systems using very different techniques for different settings, ranging from adding noise to the data with centralized filterin...
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ژورنال
عنوان ژورنال: Computing
سال: 2015
ISSN: 0010-485X,1436-5057
DOI: 10.1007/s00607-015-0451-z