Preserving privacy in joining recommender systems

Chia Lung Albert Hsieh, Justin Zhan, Dajun Zeng, Feiyue Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

In the E-commerce era, recommender system is introduced to share customer experience and comments. At the same time, there is a need for E-commerce entities to join their recommender system databases to enhance the reliability toward prospective customers and also to maximize the precision of target marketing. However, there will be a privacy disclosure hazard while joining recommender system databases. In order to preserve privacy in merging recommender system databases, we design a novel algorithm based on ElGamal scheme of homomorphic encryption.

Original languageEnglish (US)
Title of host publicationProceedings of the 2nd International Conference on Information Security and Assurance, ISA 2008
Pages561-566
Number of pages6
DOIs
Publication statusPublished - 2008
Event2nd International Conference on Information Security and Assurance, ISA 2008 - Busan, Korea, Republic of
Duration: Apr 24 2008Apr 26 2008

Other

Other2nd International Conference on Information Security and Assurance, ISA 2008
CountryKorea, Republic of
CityBusan
Period4/24/084/26/08

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ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems and Management
  • Electrical and Electronic Engineering
  • Communication

Cite this

Hsieh, C. L. A., Zhan, J., Zeng, D., & Wang, F. (2008). Preserving privacy in joining recommender systems. In Proceedings of the 2nd International Conference on Information Security and Assurance, ISA 2008 (pp. 561-566). [4511628] https://doi.org/10.1109/ISA.2008.101