Industrial Oriented Evaluation of Fuzzing Techniques

Mingzhe Wang; Jie Liang; Chijin Zhou; Yuanliang Chen; Zhiyong Wu; Yu Jiang

doi:10.1109/ICST49551.2021.00043

Industrial Oriented Evaluation of Fuzzing Techniques

Mingzhe Wang
, Jie Liang
, Chijin Zhou
, Yuanliang Chen
, Zhiyong Wu
, Yu Jiang

Tsinghua University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

uzzing is a promising method for discovering vulnerabilities. Recently, various techniques are developed to improve the efficiency of fuzzing, and impressive gains are observed in evaluation results. However, evaluation is complex, as many factors affect the results, for example, test suites, baseline and metrics. Even more, most experiment setups are lab-oriented, lacking industrial settings such as large code-base and parallel runs. The correlation between the academic evaluation results and the bug-finding ability in real industrial settings has not been sufficiently studied.

Original language	English
Title of host publication	Proceedings - 2021 IEEE 14th International Conference on Software Testing, Verification and Validation, ICST 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	306-317
Number of pages	12
ISBN (Electronic)	9781728168364
DOIs	https://doi.org/10.1109/ICST49551.2021.00043
State	Published - Apr 2021
Externally published	Yes
Event	14th IEEE International Conference on Software Testing, Verification and Validation, ICST 2021 - Virtual, Porto de Galinhas, Brazil Duration: 12 Apr 2021 → 16 Apr 2021

Publication series

Name	Proceedings - 2021 IEEE 14th International Conference on Software Testing, Verification and Validation, ICST 2021

Conference

Conference	14th IEEE International Conference on Software Testing, Verification and Validation, ICST 2021
Country/Territory	Brazil
City	Virtual, Porto de Galinhas
Period	12/04/21 → 16/04/21

Keywords

Fuzzing Optimizations
Industry Settings
Pitfalls and Solutions

Access to Document

10.1109/ICST49551.2021.00043

Cite this

Wang, M., Liang, J., Zhou, C., Chen, Y., Wu, Z., & Jiang, Y. (2021). Industrial Oriented Evaluation of Fuzzing Techniques. In Proceedings - 2021 IEEE 14th International Conference on Software Testing, Verification and Validation, ICST 2021 (pp. 306-317). Article 9438558 (Proceedings - 2021 IEEE 14th International Conference on Software Testing, Verification and Validation, ICST 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICST49551.2021.00043

Wang, Mingzhe ; Liang, Jie ; Zhou, Chijin et al. / Industrial Oriented Evaluation of Fuzzing Techniques. Proceedings - 2021 IEEE 14th International Conference on Software Testing, Verification and Validation, ICST 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 306-317 (Proceedings - 2021 IEEE 14th International Conference on Software Testing, Verification and Validation, ICST 2021).

@inproceedings{264ee9e35bca4b91b41f19147db203c2,

title = "Industrial Oriented Evaluation of Fuzzing Techniques",

abstract = "uzzing is a promising method for discovering vulnerabilities. Recently, various techniques are developed to improve the efficiency of fuzzing, and impressive gains are observed in evaluation results. However, evaluation is complex, as many factors affect the results, for example, test suites, baseline and metrics. Even more, most experiment setups are lab-oriented, lacking industrial settings such as large code-base and parallel runs. The correlation between the academic evaluation results and the bug-finding ability in real industrial settings has not been sufficiently studied.",

keywords = "Fuzzing Optimizations, Industry Settings, Pitfalls and Solutions",

author = "Mingzhe Wang and Jie Liang and Chijin Zhou and Yuanliang Chen and Zhiyong Wu and Yu Jiang",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 14th IEEE International Conference on Software Testing, Verification and Validation, ICST 2021 ; Conference date: 12-04-2021 Through 16-04-2021",

year = "2021",

month = apr,

doi = "10.1109/ICST49551.2021.00043",

language = "英语",

series = "Proceedings - 2021 IEEE 14th International Conference on Software Testing, Verification and Validation, ICST 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "306--317",

booktitle = "Proceedings - 2021 IEEE 14th International Conference on Software Testing, Verification and Validation, ICST 2021",

address = "美国",

}

Wang, M, Liang, J, Zhou, C, Chen, Y, Wu, Z & Jiang, Y 2021, Industrial Oriented Evaluation of Fuzzing Techniques. in Proceedings - 2021 IEEE 14th International Conference on Software Testing, Verification and Validation, ICST 2021., 9438558, Proceedings - 2021 IEEE 14th International Conference on Software Testing, Verification and Validation, ICST 2021, Institute of Electrical and Electronics Engineers Inc., pp. 306-317, 14th IEEE International Conference on Software Testing, Verification and Validation, ICST 2021, Virtual, Porto de Galinhas, Brazil, 12/04/21. https://doi.org/10.1109/ICST49551.2021.00043

Industrial Oriented Evaluation of Fuzzing Techniques. / Wang, Mingzhe; Liang, Jie; Zhou, Chijin et al.
Proceedings - 2021 IEEE 14th International Conference on Software Testing, Verification and Validation, ICST 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 306-317 9438558 (Proceedings - 2021 IEEE 14th International Conference on Software Testing, Verification and Validation, ICST 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Industrial Oriented Evaluation of Fuzzing Techniques

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AU - Liang, Jie

AU - Zhou, Chijin

AU - Chen, Yuanliang

AU - Wu, Zhiyong

AU - Jiang, Yu

PY - 2021/4

Y1 - 2021/4

N2 - uzzing is a promising method for discovering vulnerabilities. Recently, various techniques are developed to improve the efficiency of fuzzing, and impressive gains are observed in evaluation results. However, evaluation is complex, as many factors affect the results, for example, test suites, baseline and metrics. Even more, most experiment setups are lab-oriented, lacking industrial settings such as large code-base and parallel runs. The correlation between the academic evaluation results and the bug-finding ability in real industrial settings has not been sufficiently studied.

AB - uzzing is a promising method for discovering vulnerabilities. Recently, various techniques are developed to improve the efficiency of fuzzing, and impressive gains are observed in evaluation results. However, evaluation is complex, as many factors affect the results, for example, test suites, baseline and metrics. Even more, most experiment setups are lab-oriented, lacking industrial settings such as large code-base and parallel runs. The correlation between the academic evaluation results and the bug-finding ability in real industrial settings has not been sufficiently studied.

KW - Fuzzing Optimizations

KW - Industry Settings

KW - Pitfalls and Solutions

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U2 - 10.1109/ICST49551.2021.00043

DO - 10.1109/ICST49551.2021.00043

M3 - 会议稿件

AN - SCOPUS:85107970736

T3 - Proceedings - 2021 IEEE 14th International Conference on Software Testing, Verification and Validation, ICST 2021

SP - 306

EP - 317

BT - Proceedings - 2021 IEEE 14th International Conference on Software Testing, Verification and Validation, ICST 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 14th IEEE International Conference on Software Testing, Verification and Validation, ICST 2021

Y2 - 12 April 2021 through 16 April 2021

ER -

Wang M, Liang J, Zhou C, Chen Y, Wu Z, Jiang Y. Industrial Oriented Evaluation of Fuzzing Techniques. In Proceedings - 2021 IEEE 14th International Conference on Software Testing, Verification and Validation, ICST 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 306-317. 9438558. (Proceedings - 2021 IEEE 14th International Conference on Software Testing, Verification and Validation, ICST 2021). doi: 10.1109/ICST49551.2021.00043

Industrial Oriented Evaluation of Fuzzing Techniques

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Keywords

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