Chao Feng

Orcid: 0000-0003-0884-5457

Affiliations:
  • National University of Defense Technology (NUDT), College of Electronic Science, Changsha, China (PhD 2011)


According to our database1, Chao Feng authored at least 25 papers between 2016 and 2025.

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Bibliography

2025
Practical Object-Level Sanitizer with Aggregated Memory Access and Custom Allocator.
Proceedings of the 47th IEEE/ACM International Conference on Software Engineering, 2025

2024
OSmart: Whitebox Program Option Fuzzing.
Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security, 2024

2023
Automated Exploitable Heap Layout Generation for Heap Overflows Through Manipulation Distance-Guided Fuzzing.
Proceedings of the 32nd USENIX Security Symposium, 2023

Towards Automatic and Precise Heap Layout Manipulation for General-Purpose Programs.
Proceedings of the 30th Annual Network and Distributed System Security Symposium, 2023

2022
Pusher: an augmented fuzzer based on the connection between input and comparison operand.
Frontiers Comput. Sci., 2022

Automated detection on the security of the linked-list operations.
Frontiers Comput. Sci., 2022

Default: Mutual Information-based Crash Triage for Massive Crashes.
Proceedings of the 44th IEEE/ACM 44th International Conference on Software Engineering, 2022

2021
Reducing Test Cases with Attention Mechanism of Neural Networks.
Proceedings of the 30th USENIX Security Symposium, 2021

2020
A Pattern-Based Software Testing Framework for Exploitability Evaluation of Metadata Corruption Vulnerabilities.
Sci. Program., 2020

Automated Data-Processing Function Identification Using Deep Neural Network.
IEEE Access, 2020

2019
Marking Key Segment of Program Input via Attention Mechanism.
IEEE Access, 2019

NeuralTaint: A Key Segment Marking Tool Based on Neural Network.
IEEE Access, 2019

Program State Sensitive Parallel Fuzzing for Real World Software.
IEEE Access, 2019

Locating Vulnerability in Binaries Using Deep Neural Networks.
IEEE Access, 2019

A Lightweight Assisted Vulnerability Discovery Method Using Deep Neural Networks.
IEEE Access, 2019

2018
An Exploitability Analysis Technique for Binary Vulnerability Based on Automatic Exception Suppression.
Secur. Commun. Networks, 2018

Discover deeper bugs with dynamic symbolic execution and coverage-based fuzz testing.
IET Softw., 2018

Parallelization of Extracting Binary Program Execution Trace Offline.
Proceedings of the 2nd International Conference on Advances in Image Processing, 2018

A Large-scale Parallel Fuzzing System.
Proceedings of the 2nd International Conference on Advances in Image Processing, 2018

2017
S2F: Discover Hard-to-Reach Vulnerabilities by Semi-Symbolic Fuzz Testing.
Proceedings of the 13th International Conference on Computational Intelligence and Security, 2017

Improving the Cooperation of Fuzzing and Symbolic Execution by Test-cases Prioritizing.
Proceedings of the 13th International Conference on Computational Intelligence and Security, 2017

2016
Detecting integer overflow in Windows binary executables based on symbolic execution.
Proceedings of the 17th IEEE/ACIS International Conference on Software Engineering, 2016

Analyzing network protocol binary software with joint symbolic execution.
Proceedings of the 3rd International Conference on Systems and Informatics, 2016

Testing Network Protocol Binary Software with Selective Symbolic Execution.
Proceedings of the 12th International Conference on Computational Intelligence and Security, 2016

Predicting buffer overflow using semi-supervised learning.
Proceedings of the 9th International Congress on Image and Signal Processing, 2016


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