Corpus ID: 34898011

Identifying Attack Models for Secure Recommendation

@inproceedings{Burke2004IdentifyingAM,
  title={Identifying Attack Models for Secure Recommendation},
  author={R. Burke and B. Mobasher and Roman Zabicki and Runa Bhaumik},
  year={2004}
}
  • R. Burke, B. Mobasher, +1 author Runa Bhaumik
  • Published 2004
  • Computer Science
  • Publicly-accessible adaptive systems such as recommender systems present a security problem. Attackers, who cannot be readily distinguished from ordinary users, may introduce biased data in an attempt to force the system to "adapt" in a manner advantageous to them. Recent research has begun to examine the vulnerabilities of different recommendation techniques. In this paper, we outline some of the major issues in building secure recommender systems, concentrating in particular on the modeling… CONTINUE READING

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