Academic Journal
Binary protocol greybox fuzzing driven by marine predators algorithm.
| Τίτλος: | Binary protocol greybox fuzzing driven by marine predators algorithm. |
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| Συγγραφείς: | Jiang, Chuan, Hong, Zheng, Zhang, Guomin, Li, Yuxuan, Gu, Jinbang |
| Πηγή: | Cybersecurity (2523-3246); 9/9/2026, Vol. 9 Issue 1, p1-20, 20p |
| Θεματικοί όροι: | Computer software testing, Optimization algorithms, Penetration testing (Computer security), Defect tracking (Computer software development), Internet of things |
| Περίληψη: | Binary protocols are widely used in the Internet, industrial control systems, and Internet of Things applications, and vulnerabilities in their implementation can directly affect system security. Existing binary-protocol fuzzers face three practical challenges: identifying effective mutation positions in messages with implicit field boundaries, inferring mutation constraints for different protocol fields, and scheduling appropriate mutation operators to explore new program paths without generating excessive invalid test cases. This paper proposes MPAuzz, a greybox fuzzer for binary protocols driven by the Marine Predators Algorithm (MPA). MPAuzz first performs feedback-based mutation position exploration and classifies message regions as mutable, restricted, or immutable. It then formulates mutation operator scheduling as a multidimensional optimization problem, where each dimension corresponds to an operator choice for a mutation region. By simulating the staged exploration and exploitation process of MPA, MPAuzz adaptively adjusts operator combinations according to program responses and coverage feedback. Experiments on binary protocol implementations including MQTT, DTLS, DNS, and CoAP show that MPAuzz achieves an average valid-test-case ratio of 98.1%, improves branch coverage by 38.3% over AFLNet and 26.5% over StateAFL on average, and triggers the highest number of crashes across all targets. [ABSTRACT FROM AUTHOR] |
| Copyright of Cybersecurity (2523-3246) is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
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| Items | – Name: Title Label: Title Group: Ti Data: Binary protocol greybox fuzzing driven by marine predators algorithm. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Jiang%2C+Chuan%22">Jiang, Chuan</searchLink><br /><searchLink fieldCode="AR" term="%22Hong%2C+Zheng%22">Hong, Zheng</searchLink><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Guomin%22">Zhang, Guomin</searchLink><br /><searchLink fieldCode="AR" term="%22Li%2C+Yuxuan%22">Li, Yuxuan</searchLink><br /><searchLink fieldCode="AR" term="%22Gu%2C+Jinbang%22">Gu, Jinbang</searchLink> – Name: TitleSource Label: Source Group: Src Data: Cybersecurity (2523-3246); 9/9/2026, Vol. 9 Issue 1, p1-20, 20p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Computer+software+testing%22">Computer software testing</searchLink><br /><searchLink fieldCode="DE" term="%22Optimization+algorithms%22">Optimization algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Penetration+testing+%28Computer+security%29%22">Penetration testing (Computer security)</searchLink><br /><searchLink fieldCode="DE" term="%22Defect+tracking+%28Computer+software+development%29%22">Defect tracking (Computer software development)</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+of+things%22">Internet of things</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Binary protocols are widely used in the Internet, industrial control systems, and Internet of Things applications, and vulnerabilities in their implementation can directly affect system security. Existing binary-protocol fuzzers face three practical challenges: identifying effective mutation positions in messages with implicit field boundaries, inferring mutation constraints for different protocol fields, and scheduling appropriate mutation operators to explore new program paths without generating excessive invalid test cases. This paper proposes MPAuzz, a greybox fuzzer for binary protocols driven by the Marine Predators Algorithm (MPA). MPAuzz first performs feedback-based mutation position exploration and classifies message regions as mutable, restricted, or immutable. It then formulates mutation operator scheduling as a multidimensional optimization problem, where each dimension corresponds to an operator choice for a mutation region. By simulating the staged exploration and exploitation process of MPA, MPAuzz adaptively adjusts operator combinations according to program responses and coverage feedback. Experiments on binary protocol implementations including MQTT, DTLS, DNS, and CoAP show that MPAuzz achieves an average valid-test-case ratio of 98.1%, improves branch coverage by 38.3% over AFLNet and 26.5% over StateAFL on average, and triggers the highest number of crashes across all targets. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Cybersecurity (2523-3246) is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1186/s42400-026-00646-8 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 20 StartPage: 1 Subjects: – SubjectFull: Computer software testing Type: general – SubjectFull: Optimization algorithms Type: general – SubjectFull: Penetration testing (Computer security) Type: general – SubjectFull: Defect tracking (Computer software development) Type: general – SubjectFull: Internet of things Type: general Titles: – TitleFull: Binary protocol greybox fuzzing driven by marine predators algorithm. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Jiang, Chuan – PersonEntity: Name: NameFull: Hong, Zheng – PersonEntity: Name: NameFull: Zhang, Guomin – PersonEntity: Name: NameFull: Li, Yuxuan – PersonEntity: Name: NameFull: Gu, Jinbang IsPartOfRelationships: – BibEntity: Dates: – D: 09 M: 09 Text: 9/9/2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 25233246 Numbering: – Type: volume Value: 9 – Type: issue Value: 1 Titles: – TitleFull: Cybersecurity (2523-3246) Type: main |
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