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dc.contributor.authorTimchenko, Maxim
dc.date.accessioned2015-12-15T20:11:41Z
dc.date.available2015-12-15T20:11:41Z
dc.date.issued2015
dc.identifier.urihttps://hdl.handle.net/2144/13626
dc.description.abstractThe current state of the industry’s methods of collecting background data reflecting diagnostic and usage information are often opaque and require users to place a lot of trust in the entity receiving the data. For vendors, having a centralized database of potentially sensitive data is a privacy protection headache and a potential liability should a breach of that database occur. Unfortunately, high profile privacy failures are not uncommon, so many individuals and companies are understandably skeptical and choose not to contribute any information. It is a shame, since the data could be used for improving reliability, or getting stronger security, or for valuable academic research into real-world usage patterns. We propose, implement and evaluate a framework for non-realtime anonymous data collection, aggregation for analysis, and feedback. Departing from the usual “trusted core” approach, we aim to maintain reporters’ anonymity even if the centralized part of the system is compromised. We design a peer-to-peer mix network and its protocol that are tuned to the properties of background diagnostic traffic. Our system delivers data to a centralized repository while maintaining (i) source anonymity, (ii) privacy in transit, and (iii) the ability to provide analysis feedback back to the source. By removing the core’s ability to identify the source of data and to track users over time, we drastically reduce its attractiveness as a potential attack target and allow vendors to make concrete and verifiable privacy and anonymity claims.en_US
dc.language.isoen_USen_US
dc.rightsAttribution-NonCommercial 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subjectComputer engineeringen_US
dc.subjectAnonymityen_US
dc.subjectData collectionen_US
dc.subjectPeer-to-peer networksen_US
dc.subjectPrivacy-preserving systemsen_US
dc.subjectSecure information flowen_US
dc.titleA Framework for anonymous background data delivery and feedbacken_US
dc.typeThesis/Dissertation
dc.date.updated2015-10-28T07:35:40Z
etd.degree.nameMaster of Scienceen_US
etd.degree.levelmastersen_US
etd.degree.disciplineElectrical & Computer Engineeringen_US
etd.degree.grantorBoston Universityen_US


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Attribution-NonCommercial 4.0 International
Except where otherwise noted, this item's license is described as Attribution-NonCommercial 4.0 International