Shi-Feng Sun (Monash University, Australia), Ron Steinfeld (Monash University, Australia), Shangqi Lai (Monash University, Australia), Xingliang Yuan (Monash University, Australia), Amin Sakzad (Monash University, Australia), Joseph Liu (Monash University, Australia), ‪Surya Nepal‬ (Data61, CSIRO, Australia), Dawu Gu (Shanghai Jiao Tong University, China)

In Dynamic Symmetric Searchable Encryption (DSSE), forward privacy ensures that previous search queries cannot be associated with future updates, while backward privacy guarantees that subsequent search queries cannot be associated with deleted documents in the past. In this work, we propose a generic forward and backward-private DSSE scheme, which is, to the best of our knowledge, the first practical and non-interactive Type-II backward-private DSSE scheme not relying on trusted execution environments. To this end, we first introduce a new cryptographic primitive, named Symmetric Revocable Encryption (SRE), and propose a modular construction from some succinct cryptographic primitives. Then we present our DSSE scheme based on the proposed SRE, and instantiate it with lightweight symmetric primitives. At last, we implement our scheme and
compare it with the most efficient Type-II backward-private scheme to date (Demertzis et al., NDSS 2020). In a typical network environment, our result shows that the search in our scheme outperforms it by 2-11x under the same security notion.

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Xiaoyu Cao (Duke University), Minghong Fang (The Ohio State University), Jia Liu (The Ohio State University), Neil Zhenqiang Gong (Duke University)

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As Strong As Its Weakest Link: How to Break...

Kai Li (Syracuse University), Jiaqi Chen (Syracuse University), Xianghong Liu (Syracuse University), Yuzhe Tang (Syracuse University), XiaoFeng Wang (Indiana University Bloomington), Xiapu Luo (Hong Kong Polytechnic University)

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(Short) Object Removal Attacks on LiDAR-based 3D Object Detectors

Zhongyuan Hau, Kenneth Co, Soteris Demetriou, and Emil Lupu (Imperial College London) Best Short Paper Award Runner-up!

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Data Poisoning Attacks to Deep Learning Based Recommender Systems

Hai Huang (Tsinghua University), Jiaming Mu (Tsinghua University), Neil Zhenqiang Gong (Duke University), Qi Li (Tsinghua University), Bin Liu (West Virginia University), Mingwei Xu (Tsinghua University)

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