A Cross-Layer Security Monitoring Selection Algorithm Based on Traffic Prediction
Intrusion detection system (IDS) is emerging as a technology to improve the security of vehicular ad hoc network. However, the recent research on performance of IDS indicates that monitoring overhead is still a significant issue and challenge. The fundamental problem is caused by the fact that each...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2018-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8401485/ |
| _version_ | 1818645108376993792 |
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| author | Yao Yu Lei Guo Jinli Huang Fengyan Zhang Yue Zong |
| author_facet | Yao Yu Lei Guo Jinli Huang Fengyan Zhang Yue Zong |
| author_sort | Yao Yu |
| collection | DOAJ |
| description | Intrusion detection system (IDS) is emerging as a technology to improve the security of vehicular ad hoc network. However, the recent research on performance of IDS indicates that monitoring overhead is still a significant issue and challenge. The fundamental problem is caused by the fact that each node repeatedly detects adjacent nodes during operation. At the same time, monitoring results are sent to other nodes in the form of control packets, resulting in the decline of the network throughput. In this paper, we focus on selecting a bunch of monitoring nodes and propose a cross-layer security monitoring selection algorithm based on traffic prediction (CLSM-TP). Instead of repeatedly detection for each node, we select the monitoring node whose idle degree is relatively high by predicting the node's traffic based on a cross-layer vehicular ad hoc network. Moreover, the proposed algorithm leverages the mutual information and residual energy to optimize the node selection through social network analysis. The noteworthy contributions are that CLSM-TP can balance the resource consumption among all nodes and prolong the lifetime of vehicular ad hoc network to some extent. Our experimental results show that, the monitoring nodes selected by the algorithm proposed in this paper with higher idle degree preform good enough to monitor the whole vehicular ad hoc network. |
| first_indexed | 2024-12-17T00:25:30Z |
| format | Article |
| id | doaj.art-faa1e9fbb9854a99a04871b07606847c |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-17T00:25:30Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-faa1e9fbb9854a99a04871b07606847c2022-12-21T22:10:28ZengIEEEIEEE Access2169-35362018-01-016353823539110.1109/ACCESS.2018.28519938401485A Cross-Layer Security Monitoring Selection Algorithm Based on Traffic PredictionYao Yu0https://orcid.org/0000-0001-9804-7189Lei Guo1https://orcid.org/0000-0001-5946-7586Jinli Huang2Fengyan Zhang3Yue Zong4School of Computer Science and Engineering, Northeastern University, Shenyang, ChinaSchool of Computer Science and Engineering, Northeastern University, Shenyang, ChinaSchool of Computer Science and Engineering, Northeastern University, Shenyang, ChinaSchool of Computer Science and Engineering, Northeastern University, Shenyang, ChinaSchool of Computer Science and Engineering, Northeastern University, Shenyang, ChinaIntrusion detection system (IDS) is emerging as a technology to improve the security of vehicular ad hoc network. However, the recent research on performance of IDS indicates that monitoring overhead is still a significant issue and challenge. The fundamental problem is caused by the fact that each node repeatedly detects adjacent nodes during operation. At the same time, monitoring results are sent to other nodes in the form of control packets, resulting in the decline of the network throughput. In this paper, we focus on selecting a bunch of monitoring nodes and propose a cross-layer security monitoring selection algorithm based on traffic prediction (CLSM-TP). Instead of repeatedly detection for each node, we select the monitoring node whose idle degree is relatively high by predicting the node's traffic based on a cross-layer vehicular ad hoc network. Moreover, the proposed algorithm leverages the mutual information and residual energy to optimize the node selection through social network analysis. The noteworthy contributions are that CLSM-TP can balance the resource consumption among all nodes and prolong the lifetime of vehicular ad hoc network to some extent. Our experimental results show that, the monitoring nodes selected by the algorithm proposed in this paper with higher idle degree preform good enough to monitor the whole vehicular ad hoc network.https://ieeexplore.ieee.org/document/8401485/Intrusion detectionvehicle safetymonitoringnode selectiontraffic prediction |
| spellingShingle | Yao Yu Lei Guo Jinli Huang Fengyan Zhang Yue Zong A Cross-Layer Security Monitoring Selection Algorithm Based on Traffic Prediction IEEE Access Intrusion detection vehicle safety monitoring node selection traffic prediction |
| title | A Cross-Layer Security Monitoring Selection Algorithm Based on Traffic Prediction |
| title_full | A Cross-Layer Security Monitoring Selection Algorithm Based on Traffic Prediction |
| title_fullStr | A Cross-Layer Security Monitoring Selection Algorithm Based on Traffic Prediction |
| title_full_unstemmed | A Cross-Layer Security Monitoring Selection Algorithm Based on Traffic Prediction |
| title_short | A Cross-Layer Security Monitoring Selection Algorithm Based on Traffic Prediction |
| title_sort | cross layer security monitoring selection algorithm based on traffic prediction |
| topic | Intrusion detection vehicle safety monitoring node selection traffic prediction |
| url | https://ieeexplore.ieee.org/document/8401485/ |
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