Demo Data from EDBT 2026 / reviewers in the wild / expert
Endong Liu
dblp:205/1821
· DBLP profile ↗
3ranked-venue papers
1as first author
3since 2021 · last 2026
—ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author · 2 since 2021Artificial intelligence and machine learning · 1 · 1 since 2021Databases, data management, data science and information retrieval · 1 · 1 first-author · 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 |
Blockchain and cryptocurrency security · 50% Digital forensics and information hiding · 38% Privacy and data protection · 12% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Digital forensics and information hiding › cryptocurrency forensics
blockchain transaction analysis |
1.0 | 1 | 2026 | Evasion Under Blockchain Sanctions · WWW 2026 |
Privacy and data protection
anonymity |
0.3 | 1 | 2026 | Evasion Under Blockchain Sanctions · WWW 2026 |
Blockchain and cryptocurrency security › confidential transactions
privacy-preserving transaction |
0.3 | 1 | 2026 | Evasion Under Blockchain Sanctions · WWW 2026 |
Methods — techniques the papers use, named apart from their topics
transaction flow analysis · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Evasion Under Blockchain SanctionsabstractSanctioning blockchain addresses has become a common regulatory response to malicious activities. However, enforcement on permissionless blockchains remains challenging due to complex transaction flows and sophisticated fund-obfuscation techniques. Endong Liu, Mark Ryan 0001, Liyi Zhou, Pascal Berrang |
WWW | 1 |
| 2025 | A Defense Method Against Zero-Dynamics Attack on Wind Power SystemabstractAs wind power systems expand in size and complexity, the imperative for cyber security measures becomes increasingly critical, especially in light of the escalating threat posed by the zero-dynamics attack. Unfortunately, when the relative degree of a continuous-time system is greater than two and the sampling period is small, the sampled-data system will inevitably introduce unstable zeros, making it vulnerable to attackers. Meanwhile, it is difficult for traditional output-based system monitoring methods to detect such attacks. The current mainstream approach employs the generalized hold or generalized sampler to achieve zero shifting, but the implementation is challenging. In this article, we propose a defense method based on electronically tunable passive components to address this challenge. The method effectively defends against the zero-dynamics attack by introducing a gain-scheduling combined with the real-time parameter adjustment function of the electronically tunable passive components to move the unstable zeros of the system. Simulation results show that this defense method can improve the ability of the wind power system to resist zero-dynamics attack. Heng Zhang 0001, Xin Wang 0044, Chensheng Liu, Endong Liu, Jian Zhang 0082 |
IEEE Trans. Ind. Informatics | 5 |
| 2024 | UAV remote sensing detection and target recognition based on SCP-YOLO
Lihui Wang 0003, Zhan Miao, Endong Liu |
Neural Comput. Appl. | 3 |