Datashare: A Decentralized Privacy-Preserving Search Engine for Investigative Journalists
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Investigative journalists collect large numbers of digital documents during their investigations. These documents could greatly benefit other journalists' work. However, many of these documents contain sensitive information and their possession of such documents can endanger reporters, their stories, and their sources. Thus, many documents are only used only for single, local, investigations. We present Datashare, a decentralized and privacy-preserving global search system that enables journalists worldwide to find documents via a dedicated network of peers. Datashare combines well-known anonymous authentication mechanisms and anonymous communication primitives, a novel asynchronous messaging system, and a novel multi-set private set intersection protocol (MS-PSI) into a decentralized peer-to-peer private document search engine. We show that Datashare is secure and scales to thousands of users and millions of documents using a prototype implementation.
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