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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 2, 2016.
Abstract: Online social networks are popularized with people to connect friends, share resources etc. Meanwhile, the online social networks always suffer the problem of privacy exposure. The existing methods to prevent exposure are to enforce access control provided by the social network providers or social network users. However, those enforcements are impractical since one of essential goal of social network application is to share updates freely and instantly. To better the security and availability in social network applications, a novel random walking based access control of social network is proposed in this paper. Unlike using explicit attribute based match in the existing schemes, the results from random walking are employed to securely compute L1 distance between two social network users in the presented scheme, which not only avoids the leakage of private attributes, but also enables each social network user to define access control policy independently. The experimental results show that the proposed scheme can facilitate the access control for online social network.
You-sheng Zhou, En-wei Peng and Cheng-qing Guo, “A Random-Walk Based Privacy-Preserving Access Control for Online Social Networks” International Journal of Advanced Computer Science and Applications(IJACSA), 7(2), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070210
@article{Zhou2016,
title = {A Random-Walk Based Privacy-Preserving Access Control for Online Social Networks},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070210},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070210},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {2},
author = {You-sheng Zhou and En-wei Peng and Cheng-qing Guo}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.