Abstract
In recent years, the problem of privacy preservation on published social networks has become more and more important. The social media data are available on the popular on-line social network websites with rich personal information, which can be analyzed for connectivity and user behaviors. In this work, we study the problem of preserving sensitive paths in social networks. We examine the new concept called k-anonymous path privacy and propose two algorithms, based on the greedy approach with two different types of edges, namely Partially-Visited (PV) edges and None-Visited (NV) edges, which minimally perturbed the edge weights to achieve the path anonymity under different requirements. The numerical experiments showing the characteristics of the proposed algorithms are given. The results demonstrate that the proposed algorithms are feasible to achieve the k-anonymous path privacy, with different performances on directed and un-directed weighted graphs, and could be applied to different privacy requirements.
| Original language | English |
|---|---|
| Pages | 318-322 |
| Number of pages | 5 |
| DOIs | |
| Publication status | Published - 2012 Dec 12 |
| Event | 3rd International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2012 - Kaohsiung City, Taiwan Duration: 2012 Sep 26 → 2012 Sep 28 |
Other
| Other | 3rd International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2012 |
|---|---|
| Country | Taiwan |
| City | Kaohsiung City |
| Period | 12-09-26 → 12-09-28 |
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All Science Journal Classification (ASJC) codes
- Bioengineering
- Software
Cite this
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Confining edge types in K-anonymization of shortest paths. / Tsai, Yu Chuan; Wang, Shyue Liang; Kao, Hung-Yu; Hong, Tzung Pei.
2012. 318-322 Paper presented at 3rd International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2012, Kaohsiung City, Taiwan.Research output: Contribution to conference › Paper
TY - CONF
T1 - Confining edge types in K-anonymization of shortest paths
AU - Tsai, Yu Chuan
AU - Wang, Shyue Liang
AU - Kao, Hung-Yu
AU - Hong, Tzung Pei
PY - 2012/12/12
Y1 - 2012/12/12
N2 - In recent years, the problem of privacy preservation on published social networks has become more and more important. The social media data are available on the popular on-line social network websites with rich personal information, which can be analyzed for connectivity and user behaviors. In this work, we study the problem of preserving sensitive paths in social networks. We examine the new concept called k-anonymous path privacy and propose two algorithms, based on the greedy approach with two different types of edges, namely Partially-Visited (PV) edges and None-Visited (NV) edges, which minimally perturbed the edge weights to achieve the path anonymity under different requirements. The numerical experiments showing the characteristics of the proposed algorithms are given. The results demonstrate that the proposed algorithms are feasible to achieve the k-anonymous path privacy, with different performances on directed and un-directed weighted graphs, and could be applied to different privacy requirements.
AB - In recent years, the problem of privacy preservation on published social networks has become more and more important. The social media data are available on the popular on-line social network websites with rich personal information, which can be analyzed for connectivity and user behaviors. In this work, we study the problem of preserving sensitive paths in social networks. We examine the new concept called k-anonymous path privacy and propose two algorithms, based on the greedy approach with two different types of edges, namely Partially-Visited (PV) edges and None-Visited (NV) edges, which minimally perturbed the edge weights to achieve the path anonymity under different requirements. The numerical experiments showing the characteristics of the proposed algorithms are given. The results demonstrate that the proposed algorithms are feasible to achieve the k-anonymous path privacy, with different performances on directed and un-directed weighted graphs, and could be applied to different privacy requirements.
UR - http://www.scopus.com/inward/record.url?scp=84870668229&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84870668229&partnerID=8YFLogxK
U2 - 10.1109/IBICA.2012.18
DO - 10.1109/IBICA.2012.18
M3 - Paper
AN - SCOPUS:84870668229
SP - 318
EP - 322
ER -