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State of the Art Applications of Social Network Analysis pp 1–34Cite as

A Randomized Approach for Structural and Message Based Private Friend Recommendation in Online Social Networks

Part of the Lecture Notes in Social Networks book series (LNSN)

Abstract

The emerging growth of online social networks have opened new doors for various business applications such as promoting a new product across its customers. Besides this, friend recommendation is an important tool for recommending potential candidates as friends to users in order to enhance the development of the entire network structure. Existing friend recommendation methods utilize social network structure and/or user profile information. However, these techniques can no longer be applicable if the privacy of users is taken into consideration. In this chapter, we first propose a two-phase private friend recommendation protocol for recommending friends to a given target user based on the network structure as well as utilizing the real message interaction between users. Our protocol computes the recommendation scores of all users who are within a radius of h from the target user in a privacy-preserving manner. We then address some implementation details and point out an inherent security issue in the current online social networks due to the message flow information. To mitigate this issue or to provide better security, we propose an extended version of the proposed protocol using randomization technique. In addition, we show the practical applicability of our approach through empirical analysis based on different parameters.

Keywords

  • Friend Recommendation
  • Current Online Social Networks
  • Recommendation Score
  • Inherent Security Issues
  • Entire Network Structure

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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  • DOI: 10.1007/978-3-319-05912-9_1
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Notes

  1. 1.

    Note that \(h\) should always be greater than 1. Because, when \(h =1\), we have \(l=1\) which implies potential candidates who are 1-hop away from \(A\) who are already friends of \(A\).

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Acknowledgments

This material is based upon work supported by the Office of Naval Research under Award No. N000141110256 and NSF under award No. CNS-1011984.

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Authors and Affiliations

  1. Department of Computer Science, Missouri S&T Rolla, Rolla, MO, 65409, USA

    Bharath K. Samanthula & Wei Jiang

Authors
  1. Bharath K. Samanthula
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  2. Wei Jiang
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Correspondence to Bharath K. Samanthula .

Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Bilkent University, Bilkent, Turkey

    Fazli Can

  2. Department of Computer Engineering, TOBB University, Sogutozu Ankara, Turkey

    Tansel Özyer

  3. Department of Computer Engineering University Campus, Middle East Technical University, Ankara, Turkey

    Faruk Polat

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Samanthula, B.K., Jiang, W. (2014). A Randomized Approach for Structural and Message Based Private Friend Recommendation in Online Social Networks. In: Can, F., Özyer, T., Polat, F. (eds) State of the Art Applications of Social Network Analysis. Lecture Notes in Social Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-05912-9_1

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  • DOI: https://doi.org/10.1007/978-3-319-05912-9_1

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