EDBT 2026 Demo / reviewers in the wild / expert
Xiaohua Ye
dblp:292/4656
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Network and information security
1 paper |
Cryptographic primitives and cryptanalysis · 46% Privacy and data protection · 30% Systems and software security · 23% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Systems and software security › database security
encrypted database |
0.7 | 1 | 2023 | Frequency-revealing attacks against Frequency-hiding Order-preserving Encryption · Proc. VLDB Endow. 2023 |
Cryptographic primitives and cryptanalysis › encryption › property-preserving encryption › order-preserving encryption
frequency-hiding order-preserving encryption |
0.7 | 1 | 2023 | Frequency-revealing attacks against Frequency-hiding Order-preserving Encryption · Proc. VLDB Endow. 2023 |
Privacy and data protection
inference attack |
0.7 | 1 | 2023 | Frequency-revealing attacks against Frequency-hiding Order-preserving Encryption · Proc. VLDB Endow. 2023 |
Cryptographic primitives and cryptanalysis › encryption › property-preserving encryption
order-preserving encryption |
0.7 | 1 | 2023 | Frequency-revealing attacks against Frequency-hiding Order-preserving Encryption · Proc. VLDB Endow. 2023 |
Methods — techniques the papers use, named apart from their topics
inference attack · 0.7ciphertext-only attack · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Frequency-revealing attacks against Frequency-hiding Order-preserving EncryptionabstractOrder-preserving encryption (OPE) allows efficient comparison operations over encrypted data and thus is popular in encrypted databases. However, most existing OPE schemes are vulnerable to inference attacks as they leak plaintext frequency. To this end, some frequency-hiding order-preserving encryption (FH-OPE) schemes are proposed and claim to prevent the leakage of frequency. FH-OPE schemes are considered an important step towards mitigating inference attacks. Unfortunately, there are still vulnerabilities in all existing FH-OPE schemes. In this work, we revisit the security of all existing FH-OPE schemes. We are the first to demonstrate that plaintext frequency hidden by them is recoverable. We present three ciphertext-only attacks named frequency-revealing attacks to recover plaintext frequency. We evaluate our attacks in three real-world datasets. They recover over 90% of plaintext frequency hidden by any existing FH-OPE scheme. With frequency revealed, we also show the potentiality to apply inference attacks on existing FH-OPE schemes. Our findings highlight the limitations of current FH-OPE schemes. Our attacks demonstrate that achieving frequency-hiding requires addressing the leakages of both non-uniform ciphertext distribution and insertion orders of ciphertexts, even though the leakage of insertion orders is always ignored in OPE. Xinle Cao, Jian Liu 0012, Yongsheng Shen, Xiaohua Ye, Kui Ren 0001 |
Proc. VLDB Endow. | 4 |