| Title | Identical User Tracking with Behavior Pattern Analysis in Online Community |
| Publication Type | Conference Paper |
| Year of Publication | 2017 |
| Authors | Park, Sang-Hyun, Kang, Min-Suk, Yoon, So-Hye, Park, Seog |
| Conference Name | Proceedings of the Symposium on Applied Computing |
| Publisher | ACM |
| Conference Location | New York, NY, USA |
| ISBN Number | 978-1-4503-4486-9 |
| Keywords | meta heuristic, online community, privacy, pubcrawl, Resiliency, Scalability, Security Heuristics, user profiles |
| Abstract | The proliferation of mobile technology promotes social activities without time and space limitation. Users share information about their interests and preferences through a social network service, blog, or community. However, sensitive personal information may be exposed with the use of social activities. For example, a specific person can be identified according to exposure of personal information on the web. In this paper, we shows that a nickname that is used in an online community can be tracked by analysis of a user's behavior even though the nickname is changed to avoid identification. Unlike existing studies about user identification in a social network service, we focus on online community, which has not been extensively studied. We analyze characteristics of the online community and propose a method to track a user's nickname change to identify the user. We validate the proposed method using data collected from the online community. Results show that the proposed method can track the user's nickname change and link the old nickname with the new one. |
| URL | http://doi.acm.org/10.1145/3019612.3019910 |
| DOI | 10.1145/3019612.3019910 |
| Citation Key | park_identical_2017 |
Identical User Tracking with Behavior Pattern Analysis in Online Community