]> 2013-05-13T10:30:00-05:00 2013-05-13T12:00:00-05:00 In this work we describe an approach to distinguish real and impostor/ compromised accounts on social media. Compromising a user's social media account is not only a breach of security, but can also lead to dissemination of misinformation at a fast pace on social media. There have been several such high profile attacks recently, including on Twitter feeds of AP, CBS, and Delta Airlines. A fake account for the Prime Minister's Office in India was used to spread malicious rumors last year. Our approach builds a profile or footprint of users using both the content of their tweets and the structure of their network. We analyze the real time content of users (Tweets, Facebook posts, etc.) and compare them with information about the user from reliable sources on the Web (e.g., newspapers, news channels, etc.) in order to compute a similarity metric between content from the two sources. We also compute a metric based on the social network analysis of the users: who connects to them, who they are connected with, and how central they are in their network. We have shown how such an approach can easily detect fake accounts for not just well known people such as President Obama, but also for lesser known people and organizations. We also show promising initial results on how this approach can be used to detect an account which has been hacked.

Committee: Anupam Joshi (chair), Tim Finin, Tim Oates, Ponnurangam Kumaraguru (IIIT Delhi)

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