Fri, April 11, 2:00 PM
60 MINUTES
Secure and Practical Search Over Dynamic Encrypted Datasets

We address the problem of dynamic symmetric searchable encryption (DSE), where encrypted data is stored on untrusted servers, enabling efficient search and updates while minimizing information leakage. Our focus is on achieving strong privacy notions—forward privacy (preventing linking updates to past queries) and backward privacy (limiting information about deleted entries in future queries). We introduce three novel schemes to address these challenges: Mitra, a lightweight and efficient scheme with Type-II backward privacy; Orion, the first implemented scheme with stronger Type-I backward privacy; and Horus, which improves query efficiency by reducing communication overhead while maintaining Type-III backward privacy. In addition to these, we propose OSSE, the first DSE scheme to achieve asymptotically optimal search time, significantly improving performance over prior work. We also develop LLSE, a scheme that, while slightly less optimal than OSSE, achieves faster deletions, smaller server storage, and still outperforms existing solutions. Furthermore, we extend our work to multi-user DSE (DMUSSE) by introducing µSE, the first provably secure scheme in this setting, with support for blockchain-based verifiability.

Javad Ghareh Chamani

Researcher @ Huawei Hong Kong Research Center

Dr. Javad Ghareh Chamani is a distinguished researcher at the Huawei Research Center in Hong Kong, specializing in cutting-edge advancements in computer science. He earned his Ph.D. in Computer Science and Engineering from the Hong Kong University of Science and Technology (HKUST) in 2022 through a dual-degree program in collaboration with Sharif University of Technology. Prior to this, he completed his Master’s degree in Software Engineering at Sharif University of Technology and obtained his Bachelor’s degree in Software Engineering from the University of Tehran. Dr. Ghareh Chamani’s research expertise spans the fields of security and privacy, with a particular emphasis on designing innovative cryptographic protocols tailored to diverse application scenarios. His work addresses critical challenges in cloud data privacy, distributed/federated machine learning, and secure computation using trusted hardware. Additionally, he explores the development of efficient data compression algorithms for both CPU and GPU platforms. His academic and professional excellence is underscored by several notable achievements, including securing 3rd place and a bronze medal in the National Computer Engineering Olympiad in Iran in 2011 and earning 3rd place in the Blockchain Business Model Challenge in Hong Kong in 2020.