The Wireless IoT Device Identification based on Channel State Information Fingerprinting
| Autor: | Shengzhen Zhu, Zhonglin Ding, Rui Liu, Shuang Yang, Mingxuan Zhang, Yang Li |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Authentication
Computer science 010401 analytical chemistry Feature extraction Real-time computing Feature recognition 02 engineering and technology 01 natural sciences 0104 chemical sciences Constant false alarm rate Identification (information) Channel state information 0202 electrical engineering electronic engineering information engineering Test statistic 020201 artificial intelligence & image processing Communication channel |
| Zdroj: | 2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC). |
| DOI: | 10.1109/itaic49862.2020.9338751 |
| Popis: | Since the existing device identity authentication technology based on wireless signal feature extraction and recognition of the physical layer of the Internet of Things needs to make estimation assumptions on the channel model, there are significant limitations in the changing environment of the actual application scenario. In view of the above problems, this paper proposes an identity authentication mechanism for IoT devices based on channel state information (CSI) recognition. This mechanism combines a channel estimation algorithm with a channel state feature recognition algorithm. The channel-based CSI at the receiving end is used to distinguish the identity of the sender. The legal hypothesis test and the Euclidean distance between two consecutive CSIs are used as the test statistic, to realize the identity authentication of the device by judging the comparison of the statistic and the detection threshold. This mechanism can realize the identification of the access terminal without making special assumptions about the channel model. Test analysis shows that the method has low false alarm rate and missed detection rate. |
| Databáze: | OpenAIRE |
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