Directed Fuzzing Based on Bottleneck Detection-Reference-Cited by-同舟云学术

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Directed Fuzzing Based on Bottleneck Detection

Published:2024-05-24 Issue: Volume:16 Page:32-37
ISSN:
Container-title:Proceedings of the 2024 5th International Conference on Computing, Networks and Internet of Things
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Author:

Wan Yifeng¹^ORCID,Wang Wenting²^ORCID,Sun Jiajun³^ORCID,Tian Donghai³^ORCID

Affiliation:

1. School of Cyberspace Science and Technology, Beijing Institute of Technology, China

2. State Grid Shandong Electric Power Institute, China

3. School of Computer Science and Technology, Beijing Institute of Technology, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3670105.3670111

Reference18 articles.

1. Chenyang Lyu, Shouling Ji, Xuhong Zhang, Hong Liang, 2022. EMS: History-Driven Mutation for Coverage-based Fuzzing. In NDSS.

2. Driller: Augmenting fuzzing through selective symbolic execution;Stephens Nick;NDSS,2016

3. Insu Yun, Sangho Lee, Meng Xu, Yeongjin Jang, and Taesoo Kim. 2018. QSYM: A practical concolic execution engine tailored for hybrid fuzzing. In 27th USENIX Security Symposium (USENIX Security 18). 745–761.

4. Yaohui Chen, Mansour Ahmadi, Boyu Wang, Long Lu, 2020. MEUZZ: Smart Seed Scheduling for Hybrid Fuzzing. In 23rd International Symposium on Research in Attacks, Intrusions and Defenses (RAID 2020). 77–92.

5. Intriguer

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