Ioannis Demertzis (University of Maryland), Javad Ghareh Chamani (Hong Kong University of Science and Technology & Sharif University of Technology), Dimitrios Papadopoulos (Hong Kong University of Science and Technology), Charalampos Papamanthou (University of Maryland)

We study the problem of dynamic searchable encryption (DSE) with forward-and-backward privacy. Many DSE schemes have been proposed recently but the most efficient ones have one limitation: they require maintaining an operation counter for each unique keyword, either stored locally at the client or accessed obliviously (e.g., with an oblivious map) at the server, during every operation. We propose three new schemes that overcome the above limitation and achieve constant permanent client storage with improved performance, both asymptotically and experimentally, compared to prior state-of-the-art works. In particular, our first two schemes adopt a "static-to-dynamic" transformation which eliminates the need for oblivious accesses during searches. Due to this, they are the first practical schemes with minimal client storage and non-interactive search. Our third scheme is the first quasi-optimal forward-and-backward DSE scheme with only a logarithmic overhead for retrieving the query result (independently of previous deletions). While it does require an oblivious access during search in order to keep permanent client storage minimal, its practical performance is up to four orders of magnitude better than the best existing scheme with quasi-optimal search.

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DESENSITIZATION: Privacy-Aware and Attack-Preserving Crash Report

Ren Ding (Georgia Institute of Technology), Hong Hu (Georgia Institute of Technology), Wen Xu (Georgia Institute of Technology), Taesoo Kim (Georgia Institute of Technology)

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Locally Differentially Private Frequency Estimation with Consistency

Tianhao Wang (Purdue University), Milan Lopuhaä-Zwakenberg (Eindhoven University of Technology), Zitao Li (Purdue University), Boris Skoric (Eindhoven University of Technology), Ninghui Li (Purdue University)

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Finding Safety in Numbers with Secure Allegation Escrows

Venkat Arun (Massachusetts Institute of Technology), Aniket Kate (Purdue University), Deepak Garg (Max Planck Institute for Software Systems), Peter Druschel (Max Planck Institute for Software Systems), Bobby Bhattacharjee (University of Maryland)

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PhantomCache: Obfuscating Cache Conflicts with Localized Randomization

Qinhan Tan (Zhejiang University), Zhihua Zeng (Zhejiang University), Kai Bu (Zhejiang University), Kui Ren (Zhejiang University)

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