EDBT 2026 Demo / reviewers in the wild / expert
Jiansheng Ding
dblp:316/4311
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—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 protocols and secure computation · 87% Privacy and data protection · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cryptographic protocols and secure computation
neural network inference |
0.6 | 1 | 2022 | Cheetah: Lean and Fast Secure Two-Party Deep Neural Network Inference · USENIX Security Symposium 2022 |
Cryptographic protocols and secure computation › secure multiparty computation
secure two-party computation |
0.6 | 1 | 2022 | Cheetah: Lean and Fast Secure Two-Party Deep Neural Network Inference · USENIX Security Symposium 2022 |
Privacy and data protection
privacy-preserving machine learning |
0.2 | 1 | 2022 | Cheetah: Lean and Fast Secure Two-Party Deep Neural Network Inference · USENIX Security Symposium 2022 |
Methods — techniques the papers use, named apart from their topics
garbled circuits · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Cheetah: Lean and Fast Secure Two-Party Deep Neural Network Inference
Cheng Hong 0001, Jiansheng Ding |
USENIX Security Symposium | 4 |