Revealing information while preserving privacy
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
On k-anonymity and the curse of dimensionality
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Generating a privacy footprint on the internet
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
Doppelganger: Better browser privacy without the bother
Proceedings of the 13th ACM conference on Computer and communications security
Phishing and Countermeasures: Understanding the Increasing Problem of Electronic Identity Theft
Phishing and Countermeasures: Understanding the Increasing Problem of Electronic Identity Theft
Measuring privacy loss and the impact of privacy protection in web browsing
Proceedings of the 3rd symposium on Usable privacy and security
Communications of the ACM
SS'07 Proceedings of 16th USENIX Security Symposium on USENIX Security Symposium
Virtual trip lines for distributed privacy-preserving traffic monitoring
Proceedings of the 6th international conference on Mobile systems, applications, and services
Characterizing privacy in online social networks
Proceedings of the first workshop on Online social networks
Robust De-anonymization of Large Sparse Datasets
SP '08 Proceedings of the 2008 IEEE Symposium on Security and Privacy
Detecting privacy leaks using corpus-based association rules
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 18th international conference on World wide web
All your contacts are belong to us: automated identity theft attacks on social networks
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
Louis, Lester and Pierre: three protocols for location privacy
PET'07 Proceedings of the 7th international conference on Privacy enhancing technologies
Differential privacy: a survey of results
TAMC'08 Proceedings of the 5th international conference on Theory and applications of models of computation
An automatic HTTP cookie management system
Computer Networks: The International Journal of Computer and Telecommunications Networking
A Practical Attack to De-anonymize Social Network Users
SP '10 Proceedings of the 2010 IEEE Symposium on Security and Privacy
VPriv: protecting privacy in location-based vehicular services
SSYM'09 Proceedings of the 18th conference on USENIX security symposium
Multimodal location estimation
Proceedings of the international conference on Multimedia
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
An analysis of private browsing modes in modern browsers
USENIX Security'10 Proceedings of the 19th USENIX conference on Security
ICALP'06 Proceedings of the 33rd international conference on Automata, Languages and Programming - Volume Part II
Messin' with texas deriving mother's maiden names using public records
ACNS'05 Proceedings of the Third international conference on Applied Cryptography and Network Security
Prosodic and other Long-Term Features for Speaker Diarization
IEEE Transactions on Audio, Speech, and Language Processing
All your base are belong to US
Proceedings of the 2012 workshop on New security paradigms
Exploiting innocuous activity for correlating users across sites
Proceedings of the 22nd international conference on World Wide Web
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User-supplied content--in the form of photos, videos, and text--is a crucial ingredient to many web sites and services today. However, many users who provide content do not realize that their uploads may be leaking personal information in forms hard to intuitively grasp. Correlation of seemingly innocuous information can create inference chains that tell much more about individuals than they are aware of revealing. We contend that adversaries can systematically exploit such relationships by correlating information from different sources in what we term global inference attacks: assembling a comprehensive understanding from individual pieces found at a variety of locations, Sherlock-style. Not only are such attacks already technically viable given the capabilities that today's multimedia content analysis and correlation technologies readily provide, but we also find business models that provide adversaries with powerful incentives for pursuing them.