Paper 2015/1108 Original: eprint.iacr.org/2015/1108 ↗
Recommender Systems and their Security Concerns
Abstract
Instead of simply using two-dimensional $User \times Item$ features, advanced recommender systems rely on more additional dimensions (e.g. time, location, social network) in order to provide better recommendation services. In the first part of this paper, we will survey a variety of dimension features and show how they are integrated into the recommendation process. When the service providers collect more and more personal information, it brings great privacy concerns to the public. On another side, the service providers could also suffer from attacks launched by malicious users who want to bias the recommendations. In the second part of this paper, we will survey attacks from and against recommender service providers, and existing solutions.
Metadata
- Available format(s)
PDF- Category
- Applications
- Publication info
- Preprint.
- History
- 2015-11-20: last updated
- 2015-11-18: published
- Short URL
- https://ia.cr/2015/1108
- License
- https://creativecommons.org/licenses/by/4.0/
BibTeX
@misc{cryptoeprint:2015/1108,
author = {Jun Wang and Qiang Tang},
title = {Recommender Systems and their Security Concerns},
howpublished = {Cryptology {ePrint} Archive, Paper 2015/1108},
year = {2015},
url = {https://eprint.iacr.org/2015/1108}
}