Maximum bounded H-matching is Max SNP-complete
Information Processing Letters
Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
An Efficient k-Means Clustering Algorithm: Analysis and Implementation
IEEE Transactions on Pattern Analysis and Machine Intelligence
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Statistical Identification of Encrypted Web Browsing Traffic
SP '02 Proceedings of the 2002 IEEE Symposium on Security and Privacy
Incognito: efficient full-domain K-anonymity
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
L-diversity: Privacy beyond k-anonymity
ACM Transactions on Knowledge Discovery from Data (TKDD)
Remote timing attacks are practical
SSYM'03 Proceedings of the 12th conference on USENIX Security Symposium - Volume 12
Devices that tell on you: privacy trends in consumer ubiquitous computing
SS'07 Proceedings of 16th USENIX Security Symposium on USENIX Security Symposium
De-anonymizing Social Networks
SP '09 Proceedings of the 2009 30th IEEE Symposium on Security and Privacy
Physical Layer Attacks on Unlinkability in Wireless LANs
PETS '09 Proceedings of the 9th International Symposium on Privacy Enhancing Technologies
Hey, you, get off of my cloud: exploring information leakage in third-party compute clouds
Proceedings of the 16th ACM conference on Computer and communications security
Privacy-preserving data publishing: A survey of recent developments
ACM Computing Surveys (CSUR)
Side-Channel Leaks in Web Applications: A Reality Today, a Challenge Tomorrow
SP '10 Proceedings of the 2010 IEEE Symposium on Security and Privacy
Predictive black-box mitigation of timing channels
Proceedings of the 17th ACM conference on Computer and communications security
Private information disclosure from web searches
PETS'10 Proceedings of the 10th international conference on Privacy enhancing technologies
How to share your favourite search results while preserving privacy and quality
PETS'10 Proceedings of the 10th international conference on Privacy enhancing technologies
Speaker recognition in encrypted voice streams
ESORICS'10 Proceedings of the 15th European conference on Research in computer security
HCPP: Cryptography Based Secure EHR System for Patient Privacy and Emergency Healthcare
ICDCS '11 Proceedings of the 2011 31st International Conference on Distributed Computing Systems
P3CA: private anomaly detection across ISP networks
PETS'11 Proceedings of the 11th international conference on Privacy enhancing technologies
Privacy in mobile computing for location-sharing-based services
PETS'11 Proceedings of the 11th international conference on Privacy enhancing technologies
Privacy-preserving traffic padding in web-based applications
Proceedings of the 10th annual ACM workshop on Privacy in the electronic society
ICALP'06 Proceedings of the 33rd international conference on Automata, Languages and Programming - Volume Part II
ICDT'05 Proceedings of the 10th international conference on Database Theory
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While web-based applications are becoming increasingly ubiquitous, they also present new security and privacy challenges. In particular, recent research revealed that many high profile Web applications might cause private user information to leak from encrypted traffic due to side-channel attacks exploiting packet sizes and timing. Moreover, existing solutions, such as random padding and packet-size rounding, are shown to incur prohibitive cost while still not ensuring sufficient privacy protection. In this paper, we propose a novel k-indistinguishable traffic padding technique to achieve the optimal tradeoff between privacy protection and communication and computational cost. Specifically, we first present a formal model of the privacy-preserving traffic padding (PPTP). We then formulate PPTP problems under different application scenarios, analyze their complexity, and design efficient heuristic algorithms. Finally, we confirm the effectiveness and efficiency of our algorithms by comparing them to existing solutions through experiments using real-world Web applications.