A privacy-aware framework for friend recommendations in online social networks

Mona Alkanhal, Bharath K. Samanthula

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

Abstract

Online Social Networks (OSN), such as Facebook, Twitter and Tumblr, have revolutionized the way how people share information and stay connected with family and friends. Along this direction, user's privacy has been a significant concern to almost every user in the social network. In this paper, we propose a privacy-aware framework that allows users to outsource their encrypted profile data to a cloud environment. In order to achieve better security and efficiency, our framework utilizes a hybrid encryption approach that consists of Paillier's encryption scheme and AES. Also, we construct a privacy-aware friend recommendation protocol that recommends new friends to a given set of users without compromising their privacy. The proposed protocol adopts a collaborative analysis between the online social network provider and the Cloud in a privacy-preserving manner. Our proposed protocol utilizes the common neighbors approach and additive homomorphic encryption to achieve a reasonable trade-off between accuracy and security. Furthermore, we compared the performance of our protocol with existing work and show that our solution offers better functionality and security. Finally, we present experimental results evaluating the performance of our protocol and demonstrate the practical applicability of our solution.

Original languageEnglish
Title of host publicationProceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019
EditorsMeikang Qiu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages182-187
Number of pages6
ISBN (Electronic)9781728116631
DOIs
StatePublished - Aug 2019
Event22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019 - New York, United States
Duration: 1 Aug 20193 Aug 2019

Publication series

NameProceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019

Conference

Conference22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019
CountryUnited States
CityNew York
Period1/08/193/08/19

Keywords

  • Cloud Computing
  • Encryption
  • Friend Recommendation
  • Online Social Network
  • Security

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  • Cite this

    Alkanhal, M., & Samanthula, B. K. (2019). A privacy-aware framework for friend recommendations in online social networks. In M. Qiu (Ed.), Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019 (pp. 182-187). [8919589] (Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSE/EUC.2019.00043