Batching of Tasks by Users of Pseudonymous Forums: Anonymity Compromise and Protection

TL;DR

This paper investigates how batching tasks in pseudonymous forums can lead to deanonymization risks and proposes a privacy-preserving delay mechanism that balances privacy with minimal delay, validated through experiments on Wikipedia and Bitcoin data.

Contribution

It introduces a novel one-sided differential privacy framework and an optimal delay mechanism to protect against linkage attacks in batched pseudonymous activities.

Findings

Batching is common in peer review and Wikipedia edits.

The proposed delay mechanism effectively obfuscates batching.

The mechanism minimizes expected delay while preserving privacy.

Abstract

There are a number of forums where people participate under pseudonyms. One example is peer review, where the identity of reviewers for any paper is confidential. When participating in these forums, people frequently engage in "batching": executing multiple related tasks (e.g., commenting on multiple papers) at nearly the same time. Our empirical analysis shows that batching is common in two applications we consider $\unicode{x2013}$ peer review and Wikipedia edits. In this paper, we identify and address the risk of deanonymization arising from linking batched tasks. To protect against linkage attacks, we take the approach of adding delay to the posting time of batched tasks. We first show that under some natural assumptions, no delay mechanism can provide a meaningful differential privacy guarantee. We therefore propose a "one-sided" formulation of differential privacy for protecting against linkage attacks. We design a mechanism that adds zero-inflated uniform delay to events and show it can preserve privacy. We prove that this noise distribution is in fact optimal in minimizing expected delay among mechanisms adding independent noise to each event, thereby establishing the Pareto frontier of the trade-off between the expected delay for batched and unbatched events. Finally, we conduct a series of experiments on Wikipedia and Bitcoin data that corroborate the practical utility of our algorithm in obfuscating batching without introducing onerous delay to a system.