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Privacy Preserving Discovery of Nearby-Friends

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E-Technologies: Embracing the Internet of Things (MCETECH 2017)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 289))

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Abstract

We propose a privacy-preserving protocol for the discovery of nearby friends. In this scenario, Alice wants to verify whether any of her friends is close to her or not. This should be done without disclosing any information about Alice to her friends and also any of the other parties’ information to Alice. In this paper, we present a protocol based on the homomorphic property of Goldwasser-Micali cryptosystem to protect each user’s location in proximity queries. However, an active adversary could learn, if two users are “close” to each other due to the vulnerability of the Goldwasser-Micali to IND-CCA2 attacks and malleability of homomorphic encryption schemes. Our protocol solves this problem with the authenticated encryption scheme called encrypt-then-mac [5]. We implemented our proposed protocol on the Android platform and we show that the proposed system and protocol can achieve a high level of privacy and secrecy.

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Authors and Affiliations

  1. School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Canada

    Maryam Hezaveh & Carlisle Adams

Authors
  1. Maryam Hezaveh
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  2. Carlisle Adams
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Correspondence to Maryam Hezaveh .

Editor information

Editors and Affiliations

  1. Université de Montréal, Montreal, Québec, Canada

    Esma Aïmeur

  2. University of Ottawa, Ottawa, Ontario, Canada

    Umar Ruhi

  3. Carleton University, Ottawa, Ontario, Canada

    Michael Weiss

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Hezaveh, M., Adams, C. (2017). Privacy Preserving Discovery of Nearby-Friends. In: Aïmeur, E., Ruhi, U., Weiss, M. (eds) E-Technologies: Embracing the Internet of Things . MCETECH 2017. Lecture Notes in Business Information Processing, vol 289. Springer, Cham. https://doi.org/10.1007/978-3-319-59041-7_3

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  • DOI: https://doi.org/10.1007/978-3-319-59041-7_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59040-0

  • Online ISBN: 978-3-319-59041-7

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