Pengda Qiu

dblp:335/5809 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2023
0009-0004-4073-1649ORCID · reported

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

TopicWeightPapersLastEvidence papers
Network security › intrusion detection and prevention › intrusion detection
signature generation
0.712023
PackGenome: Automatically Generating Robust YARA Rules for Accurate Malware Packer Detection · CCS 2023
Malware analysis
YARA rule generation
0.712023
PackGenome: Automatically Generating Robust YARA Rules for Accurate Malware Packer Detection · CCS 2023
Systems and software security › software protection
code obfuscation
0.612022
Chosen-Instruction Attack Against Commercial Code Virtualization Obfuscators · NDSS 2022
Systems and software security
exploitation
0.612022
Chosen-Instruction Attack Against Commercial Code Virtualization Obfuscators · NDSS 2022
Systems and software security
software protection
0.612022
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
YearPublicationVenuePosition
2023 PackGenome: Automatically Generating Robust YARA Rules for Accurate Malware Packer Detection
abstract
Binary 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
CCS3
2022 Chosen-Instruction Attack Against Commercial Code Virtualization Obfuscators
Shijia Li, Chunfu Jia, Pengda Qiu, Qiyuan Chen 0006, Jiang Ming 0002, Debin Gao
NDSS3