ACM Computing Surveys· 2022Q1· Review
Fuzzing: A Survey for Roadmap
- 306citations
- Q1SCImago
- 2022year
Short summary
This survey systematically reviews fuzzing techniques, identifying gaps and solutions to guide future research and development in automated defect detection.
AI-generated from the title and abstract; the full text is not read.
Key points
- Fuzzing is effective in detecting security flaws, having found thousands of bugs and vulnerabilities.
- Key challenges in fuzzing include bridging the gap between infinite input spaces and sparse defect spaces.
- Automating the execution of diverse applications for fuzzing remains a significant hurdle.
- This survey systematically reviews existing fuzzing techniques, analyzes gaps, and proposes solutions.
AI-generated from the title and abstract; the full text is not read.
Abstract
Fuzz testing (fuzzing) has witnessed its prosperity in detecting security flaws recently. It generates a large number of test cases and monitors the executions for defects. Fuzzing has detected thousands of bugs and vulnerabilities in various applications. Although effective, there lacks systematic analysis of gaps faced by fuzzing. As a technique of defect detection, fuzzing is required to narrow down the gaps between the entire input space and the defect space. Without limitation on the generated inputs, the input space is infinite. However, defects are sparse in an application, which indicates that the defect space is much smaller than the entire input space. Besides, because fuzzing generates numerous test cases to repeatedly examine targets, it requires fuzzing to perform in an automatic manner. Due to the complexity of applications and defects, it is challenging to automatize the execution of diverse applications. In this article, we systematically review and analyze the gaps as well as their solutions, considering both breadth and depth. This survey can be a roadmap for both beginners and advanced developers to better understand fuzzing.
The authors' abstract, as published at the source. ACM Computing Surveys, 2022 · DOI ↗
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Field: Software
SoftwareComputer Science