Classification Protocols with Minimal Disclosure
Jinshuo Dong, Jason Hartline, Aravindan Vijayaraghavan

TL;DR
This paper introduces a multi-party classification protocol ensuring minimal disclosure of non-responsive documents, facilitating secure and efficient legal document review with formal guarantees for linear classifiers.
Contribution
It presents a novel multi-party classification protocol that guarantees minimal necessary disclosure and can be integrated into machine learning frameworks for secure document labeling.
Findings
Protocol guarantees minimal non-responsive disclosure
Embeds into machine learning for automated labeling
Equivalent to standard classification under certain conditions
Abstract
We consider multi-party protocols for classification that are motivated by applications such as e-discovery in court proceedings. We identify a protocol that guarantees that the requesting party receives all responsive documents and the sending party discloses the minimal amount of non-responsive documents necessary to prove that all responsive documents have been received. This protocol can be embedded in a machine learning framework that enables automated labeling of points and the resulting multi-party protocol is equivalent to the standard one-party classification problem (if the one-party classification problem satisfies a natural independence-of-irrelevant-alternatives property). Our formal guarantees focus on the case where there is a linear classifier that correctly partitions the documents.
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