Rogue Base Stations Detection for Advanced Metering Infrastructure Based on Signal Strength Clustering
The smart meters and meter collectors in Advanced Metering Infrastructure (AMI), which are installed in every home, rely on wireless Virtual Private Network (VPN) for communicating with Head End System (HES). Therefore, they are prone to suffer from malicious cyber-attack. Usually, based on General...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8793153/ |
| _version_ | 1818557753955713024 |
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| author | Qian Bin Cai Ziwen Xiao Yong Hong Liang Su Sheng |
| author_facet | Qian Bin Cai Ziwen Xiao Yong Hong Liang Su Sheng |
| author_sort | Qian Bin |
| collection | DOAJ |
| description | The smart meters and meter collectors in Advanced Metering Infrastructure (AMI), which are installed in every home, rely on wireless Virtual Private Network (VPN) for communicating with Head End System (HES). Therefore, they are prone to suffer from malicious cyber-attack. Usually, based on General Packet Radio Service (GPRS) communicated method is the most popular for meter collectors and consequently they are vulnerable to rogue Base Stations (BS) and get compromised by malicious adversaries further. Thus a Density-based spatial clustering of applications with noise (DBSCAN) method is employed to filter rogue BSs out and prevent meter collectors from attaching to them, because there is a notable difference between Signal Strength (SS) profile of legitimate BSs and rogue BSs, Numerical simulation indicates that the proposed approach is capable of detecting both stationary and moving rogue BSs online within fixed time window effectively. Moreover, the method can be implemented in existing meter collectors with limited computation resource. In conclusion, the proposed approach can enhance the level of cyber security of meter collectors. |
| first_indexed | 2024-12-14T00:03:43Z |
| format | Article |
| id | doaj.art-7548199a01fa42ddbee74cb570b643a8 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T00:03:43Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-7548199a01fa42ddbee74cb570b643a82022-12-21T23:26:09ZengIEEEIEEE Access2169-35362020-01-01815879815880510.1109/ACCESS.2019.29342228793153Rogue Base Stations Detection for Advanced Metering Infrastructure Based on Signal Strength ClusteringQian Bin0Cai Ziwen1https://orcid.org/0000-0003-0317-5204Xiao Yong2Hong Liang3Su Sheng4China Southern Power Grid, Electric Power Research Institute, Guangzhou, ChinaChina Southern Power Grid, Electric Power Research Institute, Guangzhou, ChinaChina Southern Power Grid, Electric Power Research Institute, Guangzhou, ChinaCollege of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, ChinaCollege of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, ChinaThe smart meters and meter collectors in Advanced Metering Infrastructure (AMI), which are installed in every home, rely on wireless Virtual Private Network (VPN) for communicating with Head End System (HES). Therefore, they are prone to suffer from malicious cyber-attack. Usually, based on General Packet Radio Service (GPRS) communicated method is the most popular for meter collectors and consequently they are vulnerable to rogue Base Stations (BS) and get compromised by malicious adversaries further. Thus a Density-based spatial clustering of applications with noise (DBSCAN) method is employed to filter rogue BSs out and prevent meter collectors from attaching to them, because there is a notable difference between Signal Strength (SS) profile of legitimate BSs and rogue BSs, Numerical simulation indicates that the proposed approach is capable of detecting both stationary and moving rogue BSs online within fixed time window effectively. Moreover, the method can be implemented in existing meter collectors with limited computation resource. In conclusion, the proposed approach can enhance the level of cyber security of meter collectors.https://ieeexplore.ieee.org/document/8793153/Rogue base stationcyber-attackclustering analysisadvanced metering infrastructure |
| spellingShingle | Qian Bin Cai Ziwen Xiao Yong Hong Liang Su Sheng Rogue Base Stations Detection for Advanced Metering Infrastructure Based on Signal Strength Clustering IEEE Access Rogue base station cyber-attack clustering analysis advanced metering infrastructure |
| title | Rogue Base Stations Detection for Advanced Metering Infrastructure Based on Signal Strength Clustering |
| title_full | Rogue Base Stations Detection for Advanced Metering Infrastructure Based on Signal Strength Clustering |
| title_fullStr | Rogue Base Stations Detection for Advanced Metering Infrastructure Based on Signal Strength Clustering |
| title_full_unstemmed | Rogue Base Stations Detection for Advanced Metering Infrastructure Based on Signal Strength Clustering |
| title_short | Rogue Base Stations Detection for Advanced Metering Infrastructure Based on Signal Strength Clustering |
| title_sort | rogue base stations detection for advanced metering infrastructure based on signal strength clustering |
| topic | Rogue base station cyber-attack clustering analysis advanced metering infrastructure |
| url | https://ieeexplore.ieee.org/document/8793153/ |
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