A Seed Scheduling Method With a Reinforcement Learning for a Coverage Guided Fuzzing
Seed scheduling, which determines which seed is input to the fuzzer first and the number of mutated test cases that are generated for the input seed, significantly influences crash detection performance in fuzz testing. Even for the same fuzzer, the performance in terms of detecting crashes that cau...
Main Authors: | Gyeongtaek Choi, Seungho Jeon, Jaeik Cho, Jongsub Moon |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2023-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10005088/ |
Similar Items
-
RegFuzz: A Linear Regression-Based Approach for Seed Scheduling in Directed Fuzzing
by: Mingmin Lin, et al.
Published: (2023-08-01) -
Not All Seeds Are Important: Fuzzing Guided by Untouched Edges
by: Chen Xie, et al.
Published: (2023-12-01) -
MooFuzz: Many-Objective Optimization Seed Schedule for Fuzzer
by: Xiaoqi Zhao, et al.
Published: (2021-01-01) -
InsFuzz: Fuzzing Binaries With Location Sensitivity
by: Hanfang Zhang, et al.
Published: (2019-01-01) -
SHFuzz: Selective Hybrid Fuzzing with Branch Scheduling Based on Binary Instrumentation
by: Xianya Mi, et al.
Published: (2020-08-01)