VLDB 2026 Research / reviewers in the wild / expert
Qiyuan Chen 0006
dblp:319/2575-6
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2023
0009-0009-7165-2800ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 2 · 2 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
2 papers |
Systems and software security · 57% Malware analysis · 22% Network security · 22% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Network security › intrusion detection and prevention › intrusion detection
signature generation |
0.7 | 1 | 2023 | PackGenome: Automatically Generating Robust YARA Rules for Accurate Malware Packer Detection · CCS 2023 |
Malware analysis
YARA rule generation |
0.7 | 1 | 2023 | PackGenome: Automatically Generating Robust YARA Rules for Accurate Malware Packer Detection · CCS 2023 |
Systems and software security › software protection
code obfuscation |
0.6 | 1 | 2022 | Chosen-Instruction Attack Against Commercial Code Virtualization Obfuscators · NDSS 2022 |
Systems and software security
exploitation |
0.6 | 1 | 2022 | Chosen-Instruction Attack Against Commercial Code Virtualization Obfuscators · NDSS 2022 |
Systems and software security
software protection |
0.6 | 1 | 2022 | Chosen-Instruction Attack Against Commercial Code Virtualization Obfuscators · NDSS 2022 |
Methods — techniques the papers use, named apart from their topics
program analysis · 0.7pattern extraction · 0.7chosen-instruction attack · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | PackGenome: Automatically Generating Robust YARA Rules for Accurate Malware Packer DetectionabstractBinary packing, a widely-used program obfuscation style, compresses or encrypts the original program and then recovers it at runtime. Packed malware samples are pervasive---they conceal arresting code features as unintelligible data to evade detection. To rapidly respond to large-scale packed malware, security analysts search specific binary patterns to identify corresponding packers. The quality of such packer patterns or signatures is vital to malware dissection. However, existing packer signature rules severely rely on human analysts' experience. In addition to expensive manual efforts, these human-written rules (e.g., YARA) also suffer from high false positives: as they are designed to search the pattern of bytes rather than instructions, they are very likely to mismatch with unexpected instructions. Shijia Li, Jiang Ming 0002, Pengda Qiu, Qiyuan Chen 0006, Lanqing Liu, Huaifeng Bao, Qiang Wang 0059, Chunfu Jia |
CCS | 4 |
| 2022 | Chosen-Instruction Attack Against Commercial Code Virtualization Obfuscators
Shijia Li, Chunfu Jia, Pengda Qiu, Qiyuan Chen 0006, Jiang Ming 0002, Debin Gao |
NDSS | 4 |