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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Malinka, K. Schafer, J. |
| Copyright Year | 2009 |
| Abstract | In this paper, we perform an empirical analysis of email traffic logs obtained from a large university to better understand the development of social networks. We analyzed data containing records of emails sent over a period of 10 months – the largest dataset we are aware of. We study the long term evolution of social networks on real world data. The initial analysis of data is followed by an exploration of existence of how social network impacts the anonymity. We describe possibilities of modeling social network and describe dynamics of their development. Based on our result we design attack of proper selection, which could cause higher successfulness of disclosure attacks. |
| Starting Page | 34 |
| Ending Page | 38 |
| File Size | 716383 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424438396 |
| DOI | 10.1109/ICIMP.2009.13 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-05-24 |
| Publisher Place | Italy |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Data analysis disclosure Social network services Humans Electronic mail evolution Communication system security Information technology social network Privacy Information security scale free anonymity Protection Long Term Evolution |
| Content Type | Text |
| Resource Type | Article |
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