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| Content Provider | ACM Digital Library |
|---|---|
| Author | Kim, Yu Seung Tague, Patrick Nguyen, Le T. Zhang, Joy |
| Abstract | Mobile devices have become people's indispensable companion, since they allow each individual to be constantly connected with the outside world. In order to keep connected, the devices periodically send out data, which reveal some information about the device owner. Data sent by these devices can be captured by any external observer. Since the observer can observe only the wireless data, the actual person using the device is unknown. In this work, we propose IdentityLink, an approach leveraging the captured wireless data and computer vision to infer the user-device links, i.e., inferring which device is carried by which user. Knowing the user-device links opens up new opportunities for applications such as identifying unauthorized personnel in enterprises or finding criminals by law enforcement. By conducting experiments in a realistic scenario, we demonstrate how IdentityLink can be effectively applied to real practice. |
| Starting Page | 529 |
| Ending Page | 539 |
| Page Count | 11 |
| File Format | PDF QT / MOV |
| ISBN | 9781450329682 |
| DOI | 10.1145/2632048.2636072 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2014-09-13 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Computer vision Rf sensing Identity linking |
| Content Type | Video Text |
| Resource Type | Article |
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