Practical Fault-Tolerant Data Aggregation

TL;DR

This paper critically evaluates a privacy-preserving fault-tolerant data aggregation protocol, demonstrating its low accuracy in real-world scenarios, and introduces a new, more efficient and secure protocol suitable for resource-constrained systems.

Contribution

The paper shows the limitations of a prior protocol and proposes a new, more accurate, computationally efficient, and secure data aggregation method for fault-tolerant systems.

Findings

Prior protocol has low accuracy in practical settings.

New protocol achieves high security with less computation.

The new method is suitable for resource-limited environments.

Abstract

During Financial Cryptography 2012 Chan et al. presented a novel privacy-protection fault-tolerant data aggregation protocol. Comparing to previous work, their scheme guaranteed provable privacy of individuals and could work even if some number of users refused to participate. In our paper we demonstrate that despite its merits, their method provides unacceptably low accuracy of aggregated data for a wide range of assumed parameters and cannot be used in majority of real-life systems. To show this we use both precise analytic and experimental methods. Additionally, we present a precise data aggregation protocol that provides provable level of security even facing massive failures of nodes. Moreover, the protocol requires significantly less computation (limited exploiting of heavy cryptography) than most of currently known fault tolerant aggregation protocols and offers better security guarantees that make it suitable for systems of limited resources (including sensor networks). To obtain our result we relax however the model and allow some limited communication between the nodes.