Toward the Trustworthiness of Industrial Robotics Using Differential Fuzz Testing

Simple item page
dc.contributor.authorWang, Bingqing
dc.contributor.authorWang, Rui
dc.contributor.authorSong, Houbing
dc.date.accessioned2022-11-04T16:24:09Z
dc.date.available2022-11-04T16:24:09Z
dc.date.issued2022-10-13
dc.description.abstractIntelligent robots are a current application in Industrial Internet of Things (IIoT), with their trustworthiness being a topic of considerable research interest. Vulnerabilities in robot software may affect the trustworthiness of robotics. To detect these vulnerabilities in robot software, this study proposes a differential fuzz testing method. The main idea is to continuously execute test cases for different versions of software packages to detect inconsistencies among outputs and eventually discover vulnerabilities. First, test cases are generated, combining seed generation and mutation, after which the measured model of the packages in RVIZ is built and the generated seeds are executed. The differences among inconsistent outputs are calculated and the causes of the differences analyzed. Two evaluation metrics for the inconsistencies and seeds are presented. This method is applied to the crucial package in ROS-MoveIt!. The results show that the arm.go() of moveit commander has joint angle overflow.en_US
dc.description.sponsorshipThis work was supported by the National Natural Science Foundation of China under Grants 61877040, National Key R&D Plan of China (2019YFB1309900).en_US
dc.description.urihttps://ieeexplore.ieee.org/abstract/document/9918646en_US
dc.format.extent10 pagesen_US
dc.genrejournal articlesen_US
dc.genrepostprintsen_US
dc.identifierdoi:10.13016/m2cocr-fk2n
dc.identifier.citationB. Wang, R. Wang and H. Song, "Toward the Trustworthiness of Industrial Robotics Using Differential Fuzz Testing," in IEEE Transactions on Industrial Informatics, 2022, doi: 10.1109/TII.2022.3211888.en_US
dc.identifier.urihttps://doi.org/10.1109/TII.2022.3211888
dc.identifier.urihttp://hdl.handle.net/11603/26277
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Information Systems Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rights© 2022 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.titleToward the Trustworthiness of Industrial Robotics Using Differential Fuzz Testingen_US
dc.typeTexten_US
dcterms.creatorhttps://orcid.org/0000-0003-2631-9223en_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Toward_the_Trustworthiness_of_Industrial_Robotics_Using_Differential_Fuzz_Testing.pdf
Size:
1.07 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
2.56 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

UMBC Information Systems Department
UMBC Faculty Collection