Leakage Inversion: Towards Quantifying Privacy in Searchable Encryption
Evgenios M. Kornaropoulos, Nathaniel Moyer, Charalampos Papamanthou, Alexandros Psomas
2022年份
26被引次数
10顶会引用
摘要
Searchable encryption (SE) provides cryptographic guarantees that a user can efficiently search over encrypted data while only disclosing patterns about the data, also known as leakage. Recently, the community has developed leakage-abuse attacks that shed light on what an attacker can infer about the underlying sensitive information using the aforementioned leakage. A glaring missing piece in this effort is the absence of a systematic and rigorous method that quantifies the privacy guarantees of SE.
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引用它的顶会 Paper10
- Range Search over Encrypted Multi-Attribute DataFrancesca Falzon, Evangelia Anna Markatou, Zachary Espiritu, Roberto TamassiaVLDB 2023 · 被引用 17 次
- I/O-Efficient Dynamic Searchable Encryption meets Forward & Backward PrivacyPriyanka Mondal, Javad Ghareh Chamani, Ioannis Demertzis, Dimitrios PapadopoulosUSENIX Security 2024 · 被引用 13 次
- PathGES: An Efficient and Secure Graph Encryption Scheme for Shortest Path QueriesFrancesca Falzon, Esha Ghosh, Kenneth G. Paterson, Roberto TamassiaCCS 2024 · 被引用 7 次
- Reconstructing with Even Less: Amplifying Leakage and Drawing GraphsEvangelia Anna Markatou, Roberto TamassiaCCS 2024 · 被引用 2 次
- Learning from Leakage: Database Reconstruction from Just a Few Multidimensional Range QueriesPeijie Li, Huanhuan Chen, Kaitai Liang, Evangelia Anna MarkatouNDSS 2026 · 被引用 1 次
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