arXiv subjects

Ralph Giles

Publications and source records attributed to Ralph Giles.

3 recordsLinked to original sources

arXiv2024

Nebula: Efficient, Private and Accurate Histogram Estimation

We present \textit{Nebula}, a system for differentially private histogram estimation on data distributed among clients. \textit{Nebula} allows clients to independently decide whether to participate in the system, and locally encode their data so that an untrusted server only learns data values whose multiplicity exceeds a predefined aggregation threshold, with $(\varepsilon,\delta)$ differential privacy guarantees. Compared to existing systems, \textit{Nebula} uniquely achieves: \textit{i)} a strict upper bound on client privacy leakage; \textit{ii)} significantly higher utility than standard local differential privacy systems; and \textit{iii)} no requirement for trusted third-parties, multi-party computation, or trusted hardware. We provide a formal evaluation of \textit{Nebula}'s privacy, utility and efficiency guarantees, along with an empirical assessment on three real-world datasets. On the United States Census dataset, clients can submit their data in just 0.0036 seconds and 0.0016 MB (\textbf{efficient}), under strong $(\varepsilon=1,\delta=10^{-8})$ differential privacy guarantees (\textbf{private}), enabling \textit{Nebula}'s untrusted aggregation server to estimate histograms with over 88\% better utility than existing local differential privacy deployments (\textbf{accurate}). Additionally, we describe a variant that allows clients to submit multi-dimensional data, with similar privacy, utility, and performance. Finally, we provide an implementation of \textit{Nebula}.

cs.CR↗

arXiv2023

The Boomerang protocol: A Decentralised Privacy-Preserving Verifiable Incentive Protocol

In the era of data-driven economies, incentive systems and loyalty programs, have become ubiquitous in various sectors, including advertising, retail, travel, and financial services. While these systems offer advantages for both users and companies, they necessitate the transfer and analysis of substantial amounts of sensitive data. Privacy concerns have become increasingly pertinent, necessitating the development of privacy-preserving incentive protocols. Despite the rising demand for secure and decentralised systems, the existing landscape lacks a comprehensive solution. In this work, we propose the BOOMERANG protocol, a novel decentralised privacy-preserving incentive protocol that leverages cryptographic black box accumulators to securely and privately store user interactions within the incentive system. Moreover, the protocol employs zero-knowledge proofs to transparently compute rewards for users, ensuring verifiability while preserving their privacy. To further enhance public verifiability and transparency, we utilise a smart contract on a Layer 1 blockchain to verify these zero-knowledge proofs. The careful combination of black box accumulators and zero-knowledge proofs makes the BOOMERANG protocol highly efficient.

cs.CR↗

arXiv2022

Nitriding: A tool kit for building scalable, networked, secure enclaves

Enclave deployments often fail to simultaneously be secure (e.g., resistant to side channel attacks), powerful (i.e., as fast as an off-the-shelf server), and flexible (i.e., unconstrained by development hurdles). In this paper, we present nitriding, an open tool kit that enables the development of enclave applications that satisfy all three properties. We build nitriding on top of the recently-proposed AWS Nitro Enclaves whose architecture prevents side channel attacks by design, making nitriding more secure than comparable frameworks. We abstract away the constrained development model of Nitro Enclaves, making it possible to run unmodified applications inside an enclave that have seamless and secure Internet connectivity, all while making our code user-verifiable. To demonstrate nitriding's flexibility, we design three enclave applications, each a research contribution in its own right: (i) we run a Tor bridge inside an enclave, making it resistant to protocol-level deanonymization attacks; (ii) we built a service for securely revealing infrastructure configuration, empowering users to verify privacy promises like the discarding of IP addresses at the edge; (iii) and we move a Chromium browser into an enclave, thereby isolating its attack surface from the user's system. We find that nitriding enables rapid prototyping and alleviates the deployment of production-quality systems, paving the way toward usable and secure enclaves.

cs.CR↗