Paper 2015/1108

Recommender Systems and their Security Concerns

Jun Wang and Qiang Tang

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. MINOR revision.
Keywords
recommender systemrobustnessprivacyhomomorphic encryptionmultiparty computation
Contact author(s)
qiang tang @ uni lu
History
2015-11-20: revised
2015-11-18: received
See all versions
Short URL
https://ia.cr/2015/1108
License
Creative Commons Attribution
CC BY

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},
      note = {\url{https://eprint.iacr.org/2015/1108}},
      url = {https://eprint.iacr.org/2015/1108}
}
Note: In order to protect the privacy of readers, eprint.iacr.org does not use cookies or embedded third party content.