The field of secure and efficient data sharing and search is moving towards developing innovative solutions that balance security, scalability, and performance. Recent developments have focused on improving the efficiency and expressiveness of public key authenticated encryption with keyword search, as well as optimizing search frameworks for graph-based approximate nearest neighbor search. Additionally, there is a growing interest in scaling hypergraph-based static functions and filters to trillions of keys, while also ensuring history-independent concurrent hash tables and bandwidth-efficient two-server ORAMs. Notable papers in this area include:
- Efficient and Expressive Public Key Authenticated Encryption with Keyword Search in Multi-user Scenarios, which proposes a scheme that integrates an auxiliary server to assist users in generating indexes and trapdoors, and employs the LSSS to implement expressive search.
- VSAG: An Optimized Search Framework for Graph-based Approximate Nearest Neighbor Search, which introduces an open-source framework that enhances the performance of graph-based ANNS algorithms through efficient memory access, automated parameter tuning, and efficient distance computation.
- ε-Cost Sharding: Scaling Hypergraph-Based Static Functions and Filters to Trillions of Keys, which describes a scalable implementation of static functions and filters based on hypergraphs, using ε-cost sharding to manage trillions of keys.
- History-Independent Concurrent Hash Tables, which establishes inherent bounds on the space requirements of history-independent concurrent dictionaries and presents a lock-free history-independent concurrent hash table.
- Bandwidth-Efficient Two-Server ORAMs with O(1) Client Storage, which presents two new client-friendly two-server ORAM schemes that achieve practical logarithmic bandwidth under O(1) local storage.
