Academic Journal
A High-Acceptance-Rate VxWorks Fuzzing Framework Based on Protocol Feature Fusion and Memory Extraction.
| Title: | A High-Acceptance-Rate VxWorks Fuzzing Framework Based on Protocol Feature Fusion and Memory Extraction. |
|---|---|
| Authors: | Wang, Yichuan, Han, Jiazhao, Deng, Xi, Hei, Xinhong |
| Source: | Future Internet; Aug2025, Vol. 17 Issue 8, p377, 30p |
| Subject Terms: | Embedded computer systems, Anomaly detection (Computer security), Real-time computing, Internet of things, Research protocols, Computer network security, Data extraction |
| Abstract: | With the widespread application of Internet of Things (IoT) devices, the security of embedded systems faces severe challenges. As an embedded operating system widely used in critical mission scenarios, the security of the TCP stack in VxWorks directly affects system reliability. However, existing protocol fuzzing methods based on network communication struggle to adapt to the complex state machine and grammatical rules of the TCP. Additionally, the lack of a runtime feedback mechanism for closed-source VxWorks systems leads to low testing efficiency. This paper proposes the vxTcpFuzzer framework, which generates structured test cases by integrating the field features of the TCP. Innovatively, it uses the memory data changes of VxWorks network protocol processing tasks as a coverage metric and combines a dual anomaly detection mechanism (WDB detection and heartbeat detection) to achieve precise anomaly capture. We conducted experimental evaluations on three VxWorks system devices, where vxTcpFuzzer successfully triggered multiple potential vulnerabilities, verifying the framework's effectiveness. Compared with three existing classic fuzzing schemes, vxTcpFuzzer demonstrates significant advantages in test case acceptance rates (44.94–54.92%) and test system abnormal rates (23.79–34.70%) across the three VxWorks devices. The study confirms that protocol feature fusion and memory feedback mechanisms can effectively enhance the depth and efficiency of protocol fuzzing for VxWorks systems. Furthermore, this approach offers a practical and effective solution for uncovering TCP vulnerabilities in black-box environments. [ABSTRACT FROM AUTHOR] |
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| Database: | Complementary Index |
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| Items | – Name: Title Label: Title Group: Ti Data: A High-Acceptance-Rate VxWorks Fuzzing Framework Based on Protocol Feature Fusion and Memory Extraction. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Wang%2C+Yichuan%22">Wang, Yichuan</searchLink><br /><searchLink fieldCode="AR" term="%22Han%2C+Jiazhao%22">Han, Jiazhao</searchLink><br /><searchLink fieldCode="AR" term="%22Deng%2C+Xi%22">Deng, Xi</searchLink><br /><searchLink fieldCode="AR" term="%22Hei%2C+Xinhong%22">Hei, Xinhong</searchLink> – Name: TitleSource Label: Source Group: Src Data: Future Internet; Aug2025, Vol. 17 Issue 8, p377, 30p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Embedded+computer+systems%22">Embedded computer systems</searchLink><br /><searchLink fieldCode="DE" term="%22Anomaly+detection+%28Computer+security%29%22">Anomaly detection (Computer security)</searchLink><br /><searchLink fieldCode="DE" term="%22Real-time+computing%22">Real-time computing</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+of+things%22">Internet of things</searchLink><br /><searchLink fieldCode="DE" term="%22Research+protocols%22">Research protocols</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+network+security%22">Computer network security</searchLink><br /><searchLink fieldCode="DE" term="%22Data+extraction%22">Data extraction</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: With the widespread application of Internet of Things (IoT) devices, the security of embedded systems faces severe challenges. As an embedded operating system widely used in critical mission scenarios, the security of the TCP stack in VxWorks directly affects system reliability. However, existing protocol fuzzing methods based on network communication struggle to adapt to the complex state machine and grammatical rules of the TCP. Additionally, the lack of a runtime feedback mechanism for closed-source VxWorks systems leads to low testing efficiency. This paper proposes the vxTcpFuzzer framework, which generates structured test cases by integrating the field features of the TCP. Innovatively, it uses the memory data changes of VxWorks network protocol processing tasks as a coverage metric and combines a dual anomaly detection mechanism (WDB detection and heartbeat detection) to achieve precise anomaly capture. We conducted experimental evaluations on three VxWorks system devices, where vxTcpFuzzer successfully triggered multiple potential vulnerabilities, verifying the framework's effectiveness. Compared with three existing classic fuzzing schemes, vxTcpFuzzer demonstrates significant advantages in test case acceptance rates (44.94–54.92%) and test system abnormal rates (23.79–34.70%) across the three VxWorks devices. The study confirms that protocol feature fusion and memory feedback mechanisms can effectively enhance the depth and efficiency of protocol fuzzing for VxWorks systems. Furthermore, this approach offers a practical and effective solution for uncovering TCP vulnerabilities in black-box environments. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Future Internet is the property of MDPI 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: 10.3390/fi17080377 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 30 StartPage: 377 Subjects: – SubjectFull: Embedded computer systems Type: general – SubjectFull: Anomaly detection (Computer security) Type: general – SubjectFull: Real-time computing Type: general – SubjectFull: Internet of things Type: general – SubjectFull: Research protocols Type: general – SubjectFull: Computer network security Type: general – SubjectFull: Data extraction Type: general Titles: – TitleFull: A High-Acceptance-Rate VxWorks Fuzzing Framework Based on Protocol Feature Fusion and Memory Extraction. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Wang, Yichuan – PersonEntity: Name: NameFull: Han, Jiazhao – PersonEntity: Name: NameFull: Deng, Xi – PersonEntity: Name: NameFull: Hei, Xinhong IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: Aug2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 19995903 Numbering: – Type: volume Value: 17 – Type: issue Value: 8 Titles: – TitleFull: Future Internet Type: main |
| ResultId | 1 |