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Anonymising group data sharing in opportunistic mobile social networks

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Abstract

The security and privacy risks of group users are major concerns in opportunistic mobile social network (OMSN) platforms, especially when the users share data publicly in a proximity area. However, existing schemes on group data sharing usually do not enforce the anonymity and/or privacy preservation properties and making them relatively unsuitable for large scale implementation. In this paper, we construct a compelling lightweight cryptographic encryption protocol scheme to anonymise and preserve the identity and data privacy of the users for a large scale OMSN. The users are authenticated to forward data-packet notification via Bluetooth-enabled smartphones, respond via 4G mobile network and can deny the notification with zero detection. The scheme’s notification delay considerably reduces with the introduction of some passers-by and hence achieves high reliability of packet notification forwarding in a 1000 m-squared proximity area. Simulation and testing for the performance requirement using Proverif software prove the scheme as easy to implement for large scale OMSN. Furthermore, the security analysis with proof based on the hardness of decisional bilinear Diffie–Hellman condition demonstrates the scheme as semantically secure under chosen-plaintext and chosen-ciphertext attacks. Nonetheless, resource constraints management has not been tackled in the present study.

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Funding

This work was partly supported by the National Natural Science Foundation of China [Grant Nos. 61602097, 61502087, and 61472064].

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Authors and Affiliations

  1. School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, China

    Daniel Adu-Gyamfi & Fengli Zhang

  2. Department of Cyber Security and Computer Engineering Technology, CK Tedam University of Technology and Applied Sciences, P O Box 24, Navrongo, Ghana

    Daniel Adu-Gyamfi

  3. Department of Computer Science and Informatics, University of Energy and Natural Resources, P O Box 214, Sunyani, Ghana

    Daniel Adu-Gyamfi & Augustine Takyi

Authors
  1. Daniel Adu-Gyamfi
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  2. Fengli Zhang
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Authors have contributed equally in all aspect of the manuscript in terms of design, methodology, analysis, results interpretation, manuscript writing and revision and decision to submit for publication.

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Correspondence to Daniel Adu-Gyamfi.

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Adu-Gyamfi, D., Zhang, F. & Takyi, A. Anonymising group data sharing in opportunistic mobile social networks. Wireless Netw 27, 1477–1490 (2021). https://doi.org/10.1007/s11276-020-02524-8

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