Perez, B;
Musolesi, M;
Stringhini, G;
(2018)
You are your Metadata: Identification and Obfuscation of Social Media Users using Metadata Information.
In:
Proceedings of Twelfth International AAAI Conference on Web and Social Media.
(pp. pp. 241-250).
The AAAI Press: Palo Alto, CA, USA.
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Abstract
Metadata are associated to most of the information we produce in our daily interactions and communication in the digital world. Yet, surprisingly, metadata are often still categorized as non-sensitive. Indeed, in the past, researchers and practitioners have mainly focused on the problem of the identification of a user from the content of a message. In this paper, we use Twitter as a case study to quantify the uniqueness of the association between metadata and user identity and to understand the effectiveness of potential obfuscation strategies. More specifically, we analyze atomic fields in the metadata and systematically combine them in an effort to classify new tweets as belonging to an account using different machine learning algorithms of increasing complexity. We demonstrate that, through the application of a supervised learning algorithm, we are able to identify any user in a group of 10,000 with approximately 96.7% accuracy. Moreover, if we broaden the scope of our search and consider the 10 most likely candidates we increase the accuracy of the model to 99.22%. We also found that data obfuscation is hard and ineffective for this type of data: even after perturbing 60% of the training data, it is still possible to classify users with an accuracy higher than 95%. These results have strong implications in terms of the design of metadata obfuscation strategies, for example for data set release, not only for Twitter, but, more generally, for most social media platforms.
| Type: | Proceedings paper |
|---|---|
| Title: | You are your Metadata: Identification and Obfuscation of Social Media Users using Metadata Information |
| Event: | AAAI Conference on Web and Social Media (ICWSM) |
| Location: | Palo Alto, CA |
| Dates: | 25 June 2018 - 28 June 2018 |
| ISBN-13: | 978-1-57735-798-8 |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | https://aaai.org/ocs/index.php/ICWSM/ICWSM18/paper... |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Twitter; social networks; metadata; classification; re-identification |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science UCL > Provost and Vice Provost Offices > UCL SLASH UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Geography |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10046465 |
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