Demo Data from EDBT 2026 / reviewers in the wild / expert
Seunghong Kim
dblp:291/4562
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 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 · 50% Privacy and data protection · 50% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Privacy and data protection › privacy-preserving computation
encrypted data processing |
0.5 | 1 | 2021 | Efficient Sorting of Homomorphic Encrypted Data With k-Way Sorting Network · IEEE Trans. Inf. Forensics Secur. 2021 |
Cryptographic primitives and cryptanalysis
homomorphic encryption |
0.5 | 1 | 2021 | Efficient Sorting of Homomorphic Encrypted Data With k-Way Sorting Network · IEEE Trans. Inf. Forensics Secur. 2021 |
Methods — techniques the papers use, named apart from their topics
k-way sorting network · 0.5approximate homomorphic comparison · 0.5SIMD operations · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Efficient Sorting of Homomorphic Encrypted Data With k-Way Sorting NetworkabstractIn this study, we propose an efficient sorting method for encrypted data using fully homomorphic encryption (FHE). The proposed method extends the existing 2-way sorting method by applying the k-way sorting network for any prime k to reduce the depth in terms of comparison operation from O(log22n) to O(klogk2n), thereby improving performance for k slightly larger than 2, such as k=5. We apply this method to approximate FHE which is widely used due to its efficiency of homomorphic arithmetic operations. In order to build up the k-way sorting network, the k-sorter, which sorts k-numbers with a minimal comparison depth, is used as a building block. The approximate homomorphic comparison, which is the only type of comparison working on approximate FHE, cannot be used for the construction of the k-sorter as it is because the result of the comparison is not binary, unlike the comparison in conventional bit-wise FHEs. To overcome this problem, we propose an efficient k-sorter construction utilizing the features of approximate homomorphic comparison. Also, we propose an efficient construction of a k-way sorting network using cryptographic SIMD operations. To use the proposed method most efficiently, we propose an estimation formula that finds the appropriate k that is expected to reduce the total time cost when the parameters of the approximating comparisons and the performance of the operations provided by the approximate FHE are given. We also show the implementation results of the proposed method, and it shows that sorting 56= 15625 data using 5-way sorting network can be about 23.3% faster than sorting 214= 16384 data using 2-way. Seungwan Hong 0001, Seunghong Kim, Jiheon Choi, Younho Lee, Jung Hee Cheon |
IEEE Trans. Inf. Forensics Secur. | 2 |