Wang Pengfei

Wang Pengfei

Associate Professor of Computer Security

National University of Defense Technology

Biography

Wang Pengfei is an associate professor of computer security at the Department of Network and Cyber Security, National University of Defense Technology. His research interests include system security, program analysis, vulnerability detection, and fuzzing test. He is looking for self-motivated students for collaborations on computer security research.

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Interests
  • System Security
  • Program Analysis
  • Vulnerability Detection
  • Fuzzing Test.
Education

  • PhD in Computer Science and Technology, 2018

    National University of Defense Technology

  • Visiting Scholar, 2016

    University College London

Recent News

[2024-1] Our paper “INSTILLER: Towards Efficient and Realistic RTL Fuzzing” has been accepted by IEEE TCAD.

[2023-11] Our paper “The Progress, Challenges, and Perspectives of Directed Greybox Fuzzing” has been accepted by STVR.

[2023-09] Our paper “DeepGo: Predictive Directed Greybox Fuzzing” has been accepted by NDSS 2024.

[2022-12] Our paper “VulHawk: Cross-architecture Vulnerability Detection with Entropy-based Binary Code Search” has been accepted by NDSS 2023.

[2022-11] Our paper “From Release to Rebirth: Exploiting Thanos Objects in Linux Kernel " has been accepted by IEEE TIFS.

[2022-10] Our paper “UltraFuzz: Towards Resource-saving in Distributed Fuzzing” has been accepted by IEEE TSE.

[2021-12] Our paper “MobFuzz: Adaptive Multi-objective Optimization in Gray-box Fuzzing” has been accepted by NDSS 2022.

Experience

 
 
 
 
 
Research Service
Reviewer
Jan 2014 – Present
  • IEEE TIFS, 2023
  • Computer & Security, 2022
  • Software Quality Journal, 2018/2021

Publications

Gen Zhang, Pengfei Wang, Tai Yue, Danjun Liu, Yubei Guo, Kai Lu (2024). Instiller: Towards Efficient and Realistic RTL Fuzzing. IEEE TCAD.

PDF DOI

Peihong Lin, Pengfei Wang, Xu Zhou, Wei Xie, Gen Zhang, Kai Lu (2023). DeepGo: Predictive Directed Greybox Fuzzing. NDSS 2024.

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Pengfei Wang, Xu Zhou, Tai Yue, Peihong Lin, Yingying Liu, Kai Lu (2023). The progress, challenges, and perspectives of directed greybox fuzzing. STVR.

PDF DOI

Zhenhao Luo, Pengfei Wang, Baosheng Wang, Yong Tang, Wei Xie, Xu Zhou, Dangjun Liu, Kai Lu (2022). VulHawk: Cross-architecture Vulnerability Detection with Entropy-based Binary Code Search. NDSS 2023.

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Danjun Liu, Pengfei Wang, Xu Zhou, Wei Xie, Gen Zhang, Zhenhao Luo, Tai Yue, Baosheng Wang (2022). From Release to Rebirth: Exploiting Thanos Objects in Linux Kernel. IEEE TIFS.

PDF DOI

Xu Zhou, Pengfei Wang, Chenyifan Liu, Tai Yue, Yingying Liu, Congxi Song, Kai Lu, Qidi Yin, Xu Han (2022). UltraFuzz: Towards Resource-saving in Distributed Fuzzing. IEEE TSE.

PDF DOI

Gen Zhang, Pengfei Wang, Tai Yue, Xiangdong Kong, Shan Huang, Xu Zhou, Kai Lu (2022). MobFuzz: Adaptive Multi-objective Optimization in Gray-box Fuzzing. NDSS 2022.

PDF Slides

Gen Zhang, Pengfei Wang, Tai Yue, Xu Zhou, Kai Lu (2021). MEBS: Uncovering Memory Life-Cycle Bugs in Operating System Kernels. JCST.

PDF DOI

Wei Xie, Chao Zhang, Pengfei Wang, Zhenhua Wang, Qiang Yang (2021). ARGUS: Assessing Unpatched Vulnerable Devices on the Internet via Efficient Firmware Recognition. AsiaCCS 2021.

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Xiangdong Kong, Yong Tang, Pengfei Wang, Shuning Wei, Tai Yue (2021). HashMTI: Scalable Mutation-based Taint Inference with Hash Records. SANER 2021.

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Pengfei Wang, Xu Zhou, Kai Lu (2020). Sabotaging the System Boundary: A Study of the Inter-boundary Vulnerability. JISA.

PDF DOI

Tai Yue, Pengfei Wang, Yong Tang, Enze Wang, Bo Yu, Kai Lu, Xu Zhou (2020). EcoFuzz: Adaptive Energy-Saving Greybox Fuzzing as a Variant of the Adversarial Multi-Armed Bandit. USENIX Security ‘20.

PDF Slides

Bo Yu, Pengfei Wang, Tai Yue, Yong Tang (2019). Poster: Fuzzing IoT Firmware via Multi-stage Message Generation. CCS ‘19.

PDF DOI

Pengfei Wang, Jens Krinke, Xu Zhou, Kai Lu (2019). AVPredictor: Comprehensive Prediction and Detection of Atomicity Violations. CCPE.

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Pengfei Wang, Kai Lu, Gen Li, Xu Zhou (2019). DFTracker: Detecting Double-Fetch Bugs by Multi-Taints Parallel Tracking. FCS.

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Yingqi Luo, Pengfei Wang, Xu Zhou and Kai Lu (2018). DFTinker: Detecting and Fixing Double-fetch Bugs in an Automated Way. WASA 2018.

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Kai Lu, Pengfei Wang, Gen Li, Xu Zhou (2018). Untrusted Hardware Causes Double-fetch Problems in the I/O Memory. JCST.

PDF Poster DOI

Pengfei Wang, Kai Lu, Gen Li, Xu Zhou (2018). A Survey of the Double-Fetch Vulnerabilities. CCPE.

PDF DOI

Pengfei Wang, Jens Krinke, Kai Lu, Gen Li, Steve Dodier-Lazaro (2017). How Double-Fetch Situations turn into Double-Fetch Vulnerabilities: A Study of Double Fetches in the Linux Kernel. USENIX Security ‘17.

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