Zhiwei Shang (University of Waterloo), Simon Oya (University of Waterloo), Andreas Peter (University of Twente), Florian Kerschbaum (University of Waterloo)

Searchable Symmetric Encryption (SSE) allows a data owner to securely outsource its encrypted data to a cloud server while maintaining the ability to search over it and retrieve matched documents. Most existing SSE schemes leak which documents are accessed per query, i.e., the so-called access pattern, and thus are vulnerable to attacks that can recover the database or the queried keywords. Current techniques that fully hide access patterns, such as ORAM or PIR, suffer from heavy communication or computational costs, and are not designed with search capabilities in mind. Recently, Chen et al. (INFOCOM'18) proposed an obfuscation framework for SSE that protects the access pattern in a differentially private way with a reasonable utility cost. However, this scheme always produces the same obfuscated access pattern when querying for the same keyword, and thus leaks the so-called search pattern, i.e., how many times a certain query is performed. This leakage makes the proposal vulnerable to certain database and query recovery attacks.

In this paper, we propose OSSE (Obfuscated SSE), an SSE scheme that obfuscates the access pattern independently for each query performed. This in turn hides the search pattern and makes our scheme resistant against attacks that rely on this leakage. Given certain reasonable assumptions on the database and query distribution, our scheme has smaller communication overhead than ORAM-based SSE. Furthermore, our scheme works in a single communication round and requires very small constant client-side storage. Our empirical evaluation shows that OSSE is highly effective at protecting against different query recovery attacks while keeping a reasonable utility level. Our protocol provides significantly more protection than the proposal by Chen et al. against some state-of-the-art attacks, which demonstrates the importance of hiding search patterns in designing effective privacy-preserving SSE schemes.

View More Papers

Demo #4: Attacking Tesla Model X’s Autopilot Using Compromised...

Ben Nassi (Ben-Gurion University of the Negev), Yisroel Mirsky (Ben-Gurion University of the Negev, Georgia Tech), Dudi Nassi, Raz Ben Netanel (Ben-Gurion University of the Negev), Oleg Drokin (Independent Researcher), and Yuval Elovici (Ben-Gurion University of the Negev) Best Demo Award Winner ($300 cash prize)!

Read More

PGFUZZ: Policy-Guided Fuzzing for Robotic Vehicles

Hyungsub Kim (Purdue University), Muslum Ozgur Ozmen (Purdue University), Antonio Bianchi (Purdue University), Z. Berkay Celik (Purdue University), Dongyan Xu (Purdue University)

Read More

RandRunner: Distributed Randomness from Trapdoor VDFs with Strong Uniqueness

Philipp Schindler (SBA Research), Aljosha Judmayer (SBA Research), Markus Hittmeir (SBA Research), Nicholas Stifter (SBA Research, TU Wien), Edgar Weippl (Universität Wien)

Read More

ROV++: Improved Deployable Defense against BGP Hijacking

Reynaldo Morillo (University of Connecticut), Justin Furuness (University of Connecticut), Cameron Morris (University of Connecticut), James Breslin (University of Connecticut), Amir Herzberg (University of Connecticut), Bing Wang (University of Connecticut)

Read More