Attack-detection and multi-clock source cooperation-based accurate time synchronization for PLC-AIoT in smart parks
Power Line Communications-Artificial Intelligence of Things (PLC-AIoT) combines the low cost and high coverage of PLC with the learning ability of Artificial Intelligence (AI) to provide data collection and transmission capabilities for PLC-AIoT devices in smart parks. With the development of smart...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2024-12-01
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| Series: | Digital Communications and Networks |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352864823001554 |
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| _version_ | 1846101670786760704 |
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| author | Zhigang Du Sunxuan Zhang Zijia Yao Zhenyu Zhou Muhammad Tariq |
| author_facet | Zhigang Du Sunxuan Zhang Zijia Yao Zhenyu Zhou Muhammad Tariq |
| author_sort | Zhigang Du |
| collection | DOAJ |
| description | Power Line Communications-Artificial Intelligence of Things (PLC-AIoT) combines the low cost and high coverage of PLC with the learning ability of Artificial Intelligence (AI) to provide data collection and transmission capabilities for PLC-AIoT devices in smart parks. With the development of smart parks, their emerging services require secure and accurate time synchronization of PLC-AIoT devices. However, the impact of attackers on the accuracy of time synchronization cannot be ignored. To solve the aforementioned problems, we propose a tampering attack-aware Deep Q-Network (DQN)-based time synchronization algorithm. First, we construct an abnormal clock source detection model. Then, the abnormal clock source is detected and excluded by comparing the time synchronization information between the device and the gateway. Finally, the proposed algorithm realizes the joint guarantee of high accuracy and low delay for PLC-AIoT in smart parks by intelligently selecting the multi-clock source cooperation strategy and timing weights. Simulation results show that the proposed algorithm has better time synchronization delay and accuracy performance. |
| format | Article |
| id | doaj-art-fa99892970564090958201527d3b68b0 |
| institution | Kabale University |
| issn | 2352-8648 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Digital Communications and Networks |
| spelling | doaj-art-fa99892970564090958201527d3b68b02024-12-29T04:47:34ZengKeAi Communications Co., Ltd.Digital Communications and Networks2352-86482024-12-0110617321740Attack-detection and multi-clock source cooperation-based accurate time synchronization for PLC-AIoT in smart parksZhigang Du0Sunxuan Zhang1Zijia Yao2Zhenyu Zhou3Muhammad Tariq4State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China; Corresponding author.Electrical Engineering Department, National University of Computer and Emerging Sciences, Islamabad 44000, PakistanPower Line Communications-Artificial Intelligence of Things (PLC-AIoT) combines the low cost and high coverage of PLC with the learning ability of Artificial Intelligence (AI) to provide data collection and transmission capabilities for PLC-AIoT devices in smart parks. With the development of smart parks, their emerging services require secure and accurate time synchronization of PLC-AIoT devices. However, the impact of attackers on the accuracy of time synchronization cannot be ignored. To solve the aforementioned problems, we propose a tampering attack-aware Deep Q-Network (DQN)-based time synchronization algorithm. First, we construct an abnormal clock source detection model. Then, the abnormal clock source is detected and excluded by comparing the time synchronization information between the device and the gateway. Finally, the proposed algorithm realizes the joint guarantee of high accuracy and low delay for PLC-AIoT in smart parks by intelligently selecting the multi-clock source cooperation strategy and timing weights. Simulation results show that the proposed algorithm has better time synchronization delay and accuracy performance.http://www.sciencedirect.com/science/article/pii/S2352864823001554Smart parkPower line communicationsArtificial intelligence of thingsTampering attack awarenessAbnormal clock source detectionMulti-clock source cooperation |
| spellingShingle | Zhigang Du Sunxuan Zhang Zijia Yao Zhenyu Zhou Muhammad Tariq Attack-detection and multi-clock source cooperation-based accurate time synchronization for PLC-AIoT in smart parks Digital Communications and Networks Smart park Power line communications Artificial intelligence of things Tampering attack awareness Abnormal clock source detection Multi-clock source cooperation |
| title | Attack-detection and multi-clock source cooperation-based accurate time synchronization for PLC-AIoT in smart parks |
| title_full | Attack-detection and multi-clock source cooperation-based accurate time synchronization for PLC-AIoT in smart parks |
| title_fullStr | Attack-detection and multi-clock source cooperation-based accurate time synchronization for PLC-AIoT in smart parks |
| title_full_unstemmed | Attack-detection and multi-clock source cooperation-based accurate time synchronization for PLC-AIoT in smart parks |
| title_short | Attack-detection and multi-clock source cooperation-based accurate time synchronization for PLC-AIoT in smart parks |
| title_sort | attack detection and multi clock source cooperation based accurate time synchronization for plc aiot in smart parks |
| topic | Smart park Power line communications Artificial intelligence of things Tampering attack awareness Abnormal clock source detection Multi-clock source cooperation |
| url | http://www.sciencedirect.com/science/article/pii/S2352864823001554 |
| work_keys_str_mv | AT zhigangdu attackdetectionandmulticlocksourcecooperationbasedaccuratetimesynchronizationforplcaiotinsmartparks AT sunxuanzhang attackdetectionandmulticlocksourcecooperationbasedaccuratetimesynchronizationforplcaiotinsmartparks AT zijiayao attackdetectionandmulticlocksourcecooperationbasedaccuratetimesynchronizationforplcaiotinsmartparks AT zhenyuzhou attackdetectionandmulticlocksourcecooperationbasedaccuratetimesynchronizationforplcaiotinsmartparks AT muhammadtariq attackdetectionandmulticlocksourcecooperationbasedaccuratetimesynchronizationforplcaiotinsmartparks |