@inproceedings{discovery1463996, month = {November}, publisher = {ACM}, title = {PrivEx: Private collection of traffic statistics for anonymous communication networks}, year = {2014}, journal = {Proceedings of the ACM Conference on Computer and Communications Security}, address = {New York, US}, note = {{\copyright} ACM 2014. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in the Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, http://dx.doi.org/10.1145/2660267.2660280.}, pages = {1068 -- 1079}, booktitle = {Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security}, editor = {C Dimitrakakis}, url = {http://dx.doi.org/10.1145/2660267.2660280}, author = {Elahi, T and Goldberg, I and Danezis, G}, issn = {1543-7221}, abstract = {In addition to their common use for private online communication, anonymous communication networks can also be used to circumvent censorship. However, it is difficult to determine the extent to which they are actually used for this purpose without violating the privacy of the networks' users. Knowing this extent can be useful to designers and researchers who would like to improve the performance and privacy properties of the network. To address this issue, we propose a statistical data collection system, PrivEx, for collecting egress traffic statistics from anonymous communication networks in a secure and privacy-preserving manner. Our solution is based on distributed differential privacy and secure multiparty computation; it preserves the security and privacy properties of anonymous communication networks, even in the face of adversaries that can compromise data collection nodes or coerce operators to reveal cryptographic secrets and keys. Copyright is held by the owner/author(s).} }