This work presents the challenges and opportunities for developing computing-in-memory
(CIM) accelerators to support secure graph databases (GDB). First, we examine the …

With the emerging popularity of cloud computing, the problem of how to query over
cryptographically-protected data has been widely studied. However, most existing works …

In the era of big data, graph databases have become increasingly important for NoSQL
technologies, and many systems can be modeled as graphs for semantic queries …

We propose GraphOS, a system that allows a client that owns a graph database to
outsource it to an untrusted server for storage and querying. It relies on doubly-oblivious …

Graph encryption schemes play a crucial role in facilitating secure queries on encrypted
graphs hosted on untrusted servers. With applications spanning navigation systems …

Graphs nicely capture data from various domains, allowing the computations of many
analytic tasks via graph queries. Graphs of real-world data are often large, albeit useful, and …

The widespread adoption of the Internet of Things (IoT) has resulted in a vast amount of
graph data representing relationships between entities in various applications. As data …

Due to the ever-increasing interest in using large-scale graph analytics on important
applications including security, bioinformatics, and social network analysis, achieving high …

Privacy-preserving federated graph analytics is an emerging area of research. The goal is to
run graph analytics queries over a set of devices that are organized as a graph while …

We propose graph encryption schemes that efficiently support approximate shortest distance
queries on large-scale encrypted graphs. Shortest distance queries are one of the most …