An Architecture for Privacy-Preserving Telemetry Scheme
Kenneth Odoh

TL;DR
This paper introduces a privacy-preserving telemetry aggregation system that combines local differential privacy, frequency estimation, and Oblivious HTTP to enhance data privacy during collection and analysis.
Contribution
It presents a novel architecture integrating local differential privacy with OHTTP for improved privacy guarantees in telemetry data collection.
Findings
Achieved stricter privacy safeguards compared to previous methods.
Implemented a frequency estimation system with enhanced privacy protections.
Demonstrated practical deployment with available open-source code.
Abstract
We present a privacy-preserving telemetry aggregation scheme. Our underlying frequency estimation routine works within the framework of differential privacy. The design philosophy follows a client-server architecture. Furthermore, the system uses a local differential privacy scheme where data gets randomized on the client before submitting the request to the resource server. This scheme allows for data analysis on de-identified data by carefully adding noise to prevent re-identification attacks, thereby facilitating public data release without compromising the identifiability of the individual record. This work further enhances privacy guarantees by leveraging Oblivious HTTP (OHTTP) to achieve increased privacy protection for data in transit that addresses pre-existing privacy vulnerabilities in raw HTTP. We provide an implementation that focuses on frequency estimation with a histogram…
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Taxonomy
TopicsPrivacy-Preserving Technologies in Data · Internet Traffic Analysis and Secure E-voting · Cryptography and Data Security
