Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Shen Guanxiong"'
Autor:
Shen Guanxiong, Zhang Junqing
Publikováno v:
Security and Safety, Vol 3, p 2023019 (2024)
Radio frequency fingerprint identification (RFFI) shows great potential as a means for authenticating wireless devices. As RFFI can be addressed as a classification problem, deep learning techniques are widely utilized in modern RFFI systems for thei
Externí odkaz:
https://doaj.org/article/85affbb8ff6243f1aeb9a3b4ec1acd81
In order to address the issue of limited data samples for the deployment of pre-trained models in unseen environments, this paper proposes a residual channel-based data augmentation strategy for Radio Frequency Fingerprint Identification (RFFI), coup
Externí odkaz:
http://arxiv.org/abs/2412.08885
Radio frequency fingerprint identification (RFFI) is an emerging technique for the lightweight authentication of wireless Internet of things (IoT) devices. RFFI exploits unique hardware impairments as device identifiers, and deep learning is widely d
Externí odkaz:
http://arxiv.org/abs/2308.07433
Radio frequency fingerprint identification (RFFI) can classify wireless devices by analyzing the signal distortions caused by the intrinsic hardware impairments. State-of-the-art neural networks have been adopted for RFFI. However, many neural networ
Externí odkaz:
http://arxiv.org/abs/2207.03001
Autor:
Shen, Guanxiong, Zhang, Junqing, Marshall, Alan, Woods, Roger, Cavallaro, Joseph, Chen, Liquan
Radio frequency fingerprint identification (RFFI) is an emerging device authentication technique, which exploits the hardware characteristics of the RF front-end as device identifiers. RFFI is implemented in the wireless receiver and acts to extract
Externí odkaz:
http://arxiv.org/abs/2207.02999
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:
http://arxiv.org/abs/2203.02014
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:
http://arxiv.org/abs/2111.14275
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:
http://arxiv.org/abs/2107.02867
Radio frequency fingerprint identification (RFFI) is an emerging device authentication technique that relies on intrinsic hardware characteristics of wireless devices. We designed an RFFI scheme for Long Range (LoRa) systems based on spectrogram and
Externí odkaz:
http://arxiv.org/abs/2101.01668
Publikováno v:
In Pacific-Basin Finance Journal February 2023 77