Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023)

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Generic Vulnerability Analysis Based on Large-Scale Automotive Software

Authors
Chenya Bian1, *, Yuqiao Ning1, Qingyang Wu1, Longhai Yu1, Yang Chen1
1CATARC Intelligent and Connected Technology Co., Ltd., Tianjin, China
*Corresponding author. Email: bianchenya@catarc.ac.cn
Corresponding Author
Chenya Bian
Available Online 4 September 2023.
DOI
10.2991/978-94-6463-230-9_7How to use a DOI?
Keywords
Intelligent Connected Vehicle; Automotive Software; Vulnerability Scan; Software Composition Analysis
Abstract

With the continuous development of the intelligent connected vehicle, the scale of automotive software system structure is expanding, and the possibility of security vulnerability is increasing. To improve the low adaptability of traditional vulnerability scanning tools in the ICV system environment and the inaccurate vulnerability results, this paper proposes a vulnerability scanning technology for large-scale ICV software programs. By extracting the software program, performing feature extraction and component analysis, and matching the vulnerability information of the open source vulnerability database, the technology achieves more accurate identification and judgment of the components and vulnerability information in the automotive software program, and can meet the vulnerability scanning requirements of various automotive software programs.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023)
Series
Atlantis Highlights in Social Sciences, Education and Humanities
Publication Date
4 September 2023
ISBN
978-94-6463-230-9
ISSN
2667-128X
DOI
10.2991/978-94-6463-230-9_7How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Chenya Bian
AU  - Yuqiao Ning
AU  - Qingyang Wu
AU  - Longhai Yu
AU  - Yang Chen
PY  - 2023
DA  - 2023/09/04
TI  - Generic Vulnerability Analysis Based on Large-Scale Automotive Software
BT  - Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023)
PB  - Atlantis Press
SP  - 43
EP  - 56
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-230-9_7
DO  - 10.2991/978-94-6463-230-9_7
ID  - Bian2023
ER  -