Intelligent Vulnerability Analysis for Connectivity and Critical-Area Integrity in IoV
The large-scale connectivity of Internet of Vehicles (IoV) is an important challenge for the Intelligent Transportation Systems (ITS). Intelligence vulnerability analysis is an excellent solution. However, existing methods for analyzing connectivity vulnerability have ignored the existence of critic...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9121236/ |
| _version_ | 1818874471370457088 |
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| author | Shumei Liu Yao Yu Wenjian Hu Yuhuai Peng Xiaolong Yang |
| author_facet | Shumei Liu Yao Yu Wenjian Hu Yuhuai Peng Xiaolong Yang |
| author_sort | Shumei Liu |
| collection | DOAJ |
| description | The large-scale connectivity of Internet of Vehicles (IoV) is an important challenge for the Intelligent Transportation Systems (ITS). Intelligence vulnerability analysis is an excellent solution. However, existing methods for analyzing connectivity vulnerability have ignored the existence of critical areas in the system. Due to the heterogeneities of the IoV environments and services, the failure of some specific areas may seriously damage connectivity and system performance. To this end, in this paper we focus on both the dynamic connectivity and the critical-area integrity, and propose an intelligent vulnerability analysis method to effectively identify the critical area of extreme vulnerability. Specifically, we consider an intelligent analysis scenario in which roadside servers continuously learn IoV heterogeneous environment and dynamic topology, and then translate the learning results into a flexible disruption cost problem. Based on this, we utilize the spectral partitioning method to identify the minimum-cost set of topological elements whose failure not only severely damages system connectivity but also disrupts its critical areas. Furthermore, we confirm that the identified set can be used to optimize disruption cost problem, thus intelligently improving vulnerability. Simulation results show that our proposed method can effectively identify vulnerable elements and prevent significant loss in the IoV system connectivity and performance. |
| first_indexed | 2024-12-19T13:11:08Z |
| format | Article |
| id | doaj.art-3464437d40b24f0b864e3e5f0c61edf7 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T13:11:08Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-3464437d40b24f0b864e3e5f0c61edf72022-12-21T20:19:55ZengIEEEIEEE Access2169-35362020-01-01811423911424810.1109/ACCESS.2020.30038089121236Intelligent Vulnerability Analysis for Connectivity and Critical-Area Integrity in IoVShumei Liu0https://orcid.org/0000-0001-5194-6152Yao Yu1https://orcid.org/0000-0001-9804-7189Wenjian Hu2Yuhuai Peng3https://orcid.org/0000-0001-9343-5377Xiaolong Yang4Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang, ChinaKey Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang, ChinaSchool of Computer Science and Engineering, Northeastern University, Shenyang, ChinaSchool of Computer Science and Engineering, Northeastern University, Shenyang, ChinaSchool of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, ChinaThe large-scale connectivity of Internet of Vehicles (IoV) is an important challenge for the Intelligent Transportation Systems (ITS). Intelligence vulnerability analysis is an excellent solution. However, existing methods for analyzing connectivity vulnerability have ignored the existence of critical areas in the system. Due to the heterogeneities of the IoV environments and services, the failure of some specific areas may seriously damage connectivity and system performance. To this end, in this paper we focus on both the dynamic connectivity and the critical-area integrity, and propose an intelligent vulnerability analysis method to effectively identify the critical area of extreme vulnerability. Specifically, we consider an intelligent analysis scenario in which roadside servers continuously learn IoV heterogeneous environment and dynamic topology, and then translate the learning results into a flexible disruption cost problem. Based on this, we utilize the spectral partitioning method to identify the minimum-cost set of topological elements whose failure not only severely damages system connectivity but also disrupts its critical areas. Furthermore, we confirm that the identified set can be used to optimize disruption cost problem, thus intelligently improving vulnerability. Simulation results show that our proposed method can effectively identify vulnerable elements and prevent significant loss in the IoV system connectivity and performance.https://ieeexplore.ieee.org/document/9121236/Intelligent transportation systems (ITS)Internet of Vehicles (IoV)intelligence vulnerability analysisconnectivitycritical area |
| spellingShingle | Shumei Liu Yao Yu Wenjian Hu Yuhuai Peng Xiaolong Yang Intelligent Vulnerability Analysis for Connectivity and Critical-Area Integrity in IoV IEEE Access Intelligent transportation systems (ITS) Internet of Vehicles (IoV) intelligence vulnerability analysis connectivity critical area |
| title | Intelligent Vulnerability Analysis for Connectivity and Critical-Area Integrity in IoV |
| title_full | Intelligent Vulnerability Analysis for Connectivity and Critical-Area Integrity in IoV |
| title_fullStr | Intelligent Vulnerability Analysis for Connectivity and Critical-Area Integrity in IoV |
| title_full_unstemmed | Intelligent Vulnerability Analysis for Connectivity and Critical-Area Integrity in IoV |
| title_short | Intelligent Vulnerability Analysis for Connectivity and Critical-Area Integrity in IoV |
| title_sort | intelligent vulnerability analysis for connectivity and critical area integrity in iov |
| topic | Intelligent transportation systems (ITS) Internet of Vehicles (IoV) intelligence vulnerability analysis connectivity critical area |
| url | https://ieeexplore.ieee.org/document/9121236/ |
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