A Privacy-Preserving Graph Encryption Scheme Based on Oblivious RAM
Seyni Kane, Anis Bkakria
TL;DR
This work addresses secure shortest-path queries on graphs stored on untrusted servers by preventing leakage of graph structure and query intent. It proposes TOGES, a privacy-preserving graph encryption scheme that combines Oblivious RAM (ORAM) with Trusted Execution Environments (TEEs) to achieve AP indistinguishability and QP indistinguishability for SPSP queries, with adaptive security guarantees under a leakage model $\\mathcal{L}$. Building on the GKT graph encryption framework, the authors present a basic OBGE construction and a TEEs-enhanced version, along with a formal security analysis and a practical evaluation on a real OpenStreetMap-derived Paris dataset. The results demonstrate practical performance and scalability, leveraging a server-side enclave to reduce client storage and employing recursive ORAM to fit within TEE constraints, thereby enabling private, efficient graph queries in realistic deployments.
Abstract
Graph encryption schemes play a crucial role in facilitating secure queries on encrypted graphs hosted on untrusted servers. With applications spanning navigation systems, network topology, and social networks, the need to safeguard sensitive data becomes paramount. Existing graph encryption methods, however, exhibit vulnerabilities by inadvertently revealing aspects of the graph structure and query patterns, posing threats to security and privacy. In response, we propose a novel graph encryption scheme designed to mitigate access pattern and query pattern leakage through the integration of oblivious RAM and trusted execution environment techniques, exemplified by a Trusted Execution Environment (TEE). Our solution establishes two key security objectives: (1) ensuring that adversaries, when presented with an encrypted graph, remain oblivious to any information regarding the underlying graph, and (2) achieving query indistinguishability by concealing access patterns. Additionally, we conducted experimentation to evaluate the efficiency of the proposed schemes when dealing with real-world location navigation services.