Lucene-P$^2$2: A Distributed Platform for Privacy-Preserving Text-Based Search

Information retrieval (IR) plays an essential role in daily life. However, currently deployed IR technologies, e.g., Apache Lucene – open-source search software, are insufficient when the information is protected or deemed to be private. For example, submitting a query to a publicly available search engine (e.g., Bing or Google) requires disclosing potentially delicate facts (e.g., thoughts about abortion), as well as the websites the user considers interesting. Similarly, when a private database contains sensitive information needed by the user, it cannot be searched freely. Over the past decade, various approaches, generally referred to as private information retrieval, have been proposed to obfuscate queries and responses, but they are limited in that the retrieved information is inadequate to compute relevancy. To address such limitations, this article introduces the necessary techniques to build Lucene-P
$^2$
that allows one party to discover whether a second party harbors any relevant textual information without either party disclosing any information.