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Ziqi Wei 0005

dblp:407/9600 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · unresolved

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
Systems and software security · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Systems and software security › vulnerability discovery › fuzzing
firmware fuzzing
0.912025
HouseFuzz: Service-Aware Grey-Box Fuzzing for Vulnerability Detection in Linux-Based Firmware · SP 2025
Systems and software security
firmware security
0.912025
HouseFuzz: Service-Aware Grey-Box Fuzzing for Vulnerability Detection in Linux-Based Firmware · SP 2025
Systems and software security › vulnerability discovery › fuzzing
greybox fuzzing
0.912025
HouseFuzz: Service-Aware Grey-Box Fuzzing for Vulnerability Detection in Linux-Based Firmware · SP 2025
Systems and software security
vulnerability discovery
0.912025
HouseFuzz: Service-Aware Grey-Box Fuzzing for Vulnerability Detection in Linux-Based Firmware · SP 2025
Embedded and real-time systems › embedded software
firmware
0.312025
HouseFuzz: Service-Aware Grey-Box Fuzzing for Vulnerability Detection in Linux-Based Firmware · SP 2025

Methods — techniques the papers use, named apart from their topics

service-aware fuzzing · 1.7protocol semantic analysis · 1.7multi-process emulation · 1.7
YearPublicationVenuePosition
2025 HouseFuzz: Service-Aware Grey-Box Fuzzing for Vulnerability Detection in Linux-Based Firmware
abstract
To date, grey-box fuzzing has become an essential technique to detect vulnerabilities implied in Linux-based firmware. However, existing fuzzing approaches commonly encounter three overlooked obstacles stemming from firmware service characteristics, which largely hinder the effectiveness and efficiency of vulnerability identification. Firstly, the multi-process nature of firmware services is oversimplified during both the emulation and the fuzzing procedures, limiting the scope of firmware testing. Furthermore, firmware services usually incorporate customized service protocols, which feature rich and stringent semantic constraints, causing unique challenges for input generation. To address these obstacles, this paper proposes a service-aware grey-box fuzzing tool HouseFuzz. During the firmware emulation, HouseFuzz carefully traverses the system initialization procedure for identifying those network-facing and daemon processes overlooked by existing approaches. After that, during the fuzzing procedure, HouseFuzz features a multi-process fuzzing framework, enabling the comprehensive inspection of firmware services activated via multiple processes. Furthermore, HouseFuzz leverages both offline and online firmware service analysis to capture the token-level semantic constraints of customized service protocols, based on which HouseFuzz can effectively generate high-quality test cases. In evaluation, compared to SoTA grey-box firmware fuzzing approaches, HouseFuzz identified 76% more network services, achieved 24.8% more code coverage, and detected 175% more 0-day vulnerabilities on the same firmware dataset.
Haoyu Xiao, Ziqi Wei 0005, Jiarun Dai
SP2