Oath Inc.

Microsoft Technology Licensing, LLC

Yahoo! Inc.

Verizon Media Inc.

Ian Miers

Payman Mohassel

Rui Chen

Charles Lamanna

Michael Wilde

The present teaching relates to searching encrypted data. In one example, a search request is received for encrypted documents. An encrypted query is generated based on the search request. The encrypted query is sent to a server that stores a first encrypted index and a second encrypted index. The first encrypted index maps encrypted keywords to full blocks each of which has a same size and is fully filled with encrypted document identities (IDs). The second encrypted index maps encrypted keywords to partial blocks each of which has the same size and is partially filled with encrypted document IDs. Based on the encrypted query, one or more encrypted document IDs are determined by searching against both the first encrypted index and the second encrypted index. A search result is generated based on the one or more encrypted document IDs. The search result is provided in response to the search request.

Method and system for searching encrypted data

An application asynchronously flattens a graph in a relational store to provide fast access to node relationship queries. The application may implement an algorithm that retrieves forward paths of a start node. The algorithm may also retrieve reverse paths of end node. The application may cross-join the forward and reverse paths to determine link paths connecting the start and end nodes. The application may merge the link paths with existing paths. The application may increment path reference counts. The application may store the link paths as a link between the nodes to represent a relationship between the nodes.

Asynchronously flattening graphs in relational stores

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Baltimore, MD, United States of America

Ian Miers