The Case against Accuracy Estimation for Comparing Induction Algorithms
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Robust De-anonymization of Large Sparse Datasets
SP '08 Proceedings of the 2008 IEEE Symposium on Security and Privacy
Proceedings of the 18th international conference on World wide web
Proceedings of the 18th international conference on World wide web
De-anonymizing Social Networks
SP '09 Proceedings of the 2009 30th IEEE Symposium on Security and Privacy
Large Online Social Footprints--An Emerging Threat
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 03
A Practical Attack to De-anonymize Social Network Users
SP '10 Proceedings of the 2010 IEEE Symposium on Security and Privacy
You are where you tweet: a content-based approach to geo-locating twitter users
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Abusing social networks for automated user profiling
RAID'10 Proceedings of the 13th international conference on Recent advances in intrusion detection
Relationships and data sanitization: a study in scarlet
Proceedings of the 2010 workshop on New security paradigms
Cybercasing the joint: on the privacy implications of geo-tagging
HotSec'10 Proceedings of the 5th USENIX conference on Hot topics in security
Tweets from Justin Bieber's heart: the dynamics of the location field in user profiles
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
All liaisons are dangerous when all your friends are known to us
Proceedings of the 22nd ACM conference on Hypertext and hypermedia
HotSec'11 Proceedings of the 6th USENIX conference on Hot topics in security
Anonymization of location data does not work: a large-scale measurement study
MobiCom '11 Proceedings of the 17th annual international conference on Mobile computing and networking
How unique and traceable are usernames?
PETS'11 Proceedings of the 11th international conference on Privacy enhancing technologies
"I'm eating a sandwich in Glasgow": modeling locations with tweets
Proceedings of the 3rd international workshop on Search and mining user-generated contents
Sherlock holmes' evil twin: on the impact of global inference for online privacy
Proceedings of the 2011 workshop on New security paradigms workshop
On the Feasibility of Internet-Scale Author Identification
SP '12 Proceedings of the 2012 IEEE Symposium on Security and Privacy
Deanonymizing mobility traces: using social network as a side-channel
Proceedings of the 2012 ACM conference on Computer and communications security
We know how you live: exploring the spectrum of urban lifestyles
Proceedings of the first ACM conference on Online social networks
A defence scheme against Identity Theft Attack based on multiple social networks
Expert Systems with Applications: An International Journal
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We study how potential attackers can identify accounts on different social network sites that all belong to the same user, exploiting only innocuous activity that inherently comes with posted content. We examine three specific features on Yelp, Flickr, and Twitter: the geo-location attached to a user's posts, the timestamp of posts, and the user's writing style as captured by language models. We show that among these three features the location of posts is the most powerful feature to identify accounts that belong to the same user in different sites. When we combine all three features, the accuracy of identifying Twitter accounts that belong to a set of Flickr users is comparable to that of existing attacks that exploit usernames. Our attack can identify 37% more accounts than using usernames when we instead correlate Yelp and Twitter. Our results have significant privacy implications as they present a novel class of attacks that exploit users' tendency to assume that, if they maintain different personas with different names, the accounts cannot be linked together; whereas we show that the posts themselves can provide enough information to correlate the accounts.