Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Guanxiong Shen"'
Publikováno v:
Sensors, Vol 22, Iss 9, p 3127 (2022)
As LoRaWAN is one of the most popular long-range wireless protocols among low-power IoT applications, more and more focus is shifting towards security. In particular, physical layer topics become relevant to improve the security of LoRaWAN nodes, whi
Externí odkaz:
https://doaj.org/article/3939753c02864fd18656017a9573ea5d
Autor:
Raya Alhajri, Alan Marshall, Guanxiong Shen, Miguel López-Benítez, Valerio Selis, Junqing Zhang
Publikováno v:
2022 International Conference on Artificial Intelligence of Things (ICAIoT).
Publikováno v:
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
Radio frequency fingerprint identification (RFFI) is an emerging device authentication technique that relies on the intrinsic hardware characteristics of wireless devices. This paper designs a deep learning-based RFFI scheme for Long Range (LoRa) sys
Radio frequency fingerprint identification (RFFI) can classify wireless devices by analyzing the signal distortions caused by intrinsic hardware impairments. Recently, state-of-the-art neural networks have been adopted for RFFI. However, many neural
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c5b3d6ef02c940f88a653f3672f87476
http://arxiv.org/abs/2207.03001
http://arxiv.org/abs/2207.03001
Publikováno v:
Pacific-Basin Finance Journal. 77:101929
Wi-Fi sensing can classify human activities because each activity causes unique changes to the channel state information (CSI). Existing WiFi sensing suffers from limited scalability as the system needs to be retrained whenever new activities are add
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a78c83fe7da69625427489d74de2b948
Publikováno v:
IEEE Transactions on Information Forensics and Security
Radio frequency fingerprint identification (RFFI) is a promising device authentication technique based on the transmitter hardware impairments. In this paper, we propose a scalable and robust RFFI framework achieved by deep learning powered radio fre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3023864153643f417988f57d19d8c238
http://arxiv.org/abs/2107.02867
http://arxiv.org/abs/2107.02867
Radio frequency fingerprint identification (RFFI) can uniquely classify wireless devices by analyzing the received signal distortions caused by the intrinsic hardware impairments. The state-of-the-art deep learning techniques such as convolutional ne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a5c38993b8f31c9e2eed3cbef9ab86b2