Distributed Anonymous Data Collection and Feedback
Speaker/Bio
Ari Trachtenberg is a Professor of Electrical and Computer Engineering at Boston University.
Abstract
Diagnostic, usage, and statistical data collection occurs continuously in the background on our computers and smart devices. However, the privacy and anonymity of the process
or of the resulting data set are seldom given much thought
by device owners. We propose and are in the process of
implementing and evaluating a framework for non-realtime
anonymous data collection, aggregation for analysis, and
feedback. Departing from the usual \x93trusted core\x94 approach,
we aim to maintain the reporter\x92s anonymity, even if the core
of the system is compromised. We design a peer-to-peer mix
network tuned to carry data to a centralized repository while
maintaining (i) source anonymity, (ii) privacy in transit, (iii)
the ability to provide feedback from central server to source.
This is work done by Max Timchenko as part of his MS thesis, advised by Ari Trachtenberg.
Reference
- Maxim Timchenko and Ari Trachtenberg. Distributed anonymous data collection and feedback. In Proceedings of the 8th ACM International Systems and Storage Conference (SYSTOR '15). Available here.