Membership Inference Attacks Against Recommender Systems
Minxing Zhang, Zhaochun Ren, Zihan Wang, Pengjie Ren, Zhunmin Chen, Pengfei Hu, Yang Zhang
Abstract
Recently, recommender systems have achieved promising performances and become one of the most widely used web applications. However, recommender systems are often trained on highly sensitive user data, thus potential data leakage from recommender systems may lead to severe privacy problems.
Topics & Concepts
Recommender systemComputer scienceInferenceInformation retrievalWorld Wide WebArtificial intelligencePrivacy-Preserving Technologies in DataCryptography and Data SecurityRecommender Systems and Techniques