Radio Frequency Signal Identification Using Transfer Learning Based on LSTM
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Radio Frequency Signal Identification Using Transfer Learning Based on LSTM Xueli Wang1 · Yufeng Zhang1 · Hongxin Zhang2 · Yixuan Li1 · Xiaofeng Wei2 Received: 26 June 2019 / Revised: 2 April 2020 / Accepted: 2 April 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Radio frequency distinct native attribute (RF-DNA) technology is very important in distinguishing RF devices. This paper presents a new method for distinguishing RF devices by combining transfer learning and long short-term memory (TL-LSTM). The main purpose of this paper is to identify which RF device sent the unknown RF signals. The data were collected from almost the same eight RF devices produced in 2011, 2014 or 2016. These RF devices emitted unintended signals at 2.4G bandwidth with frequency shift keying. The proposed method first used late production RF devices in 2011 or 2014 as source domain and transferred the trained model to target domain produced in 2016 and then used neural network LSTM model to identify the RF signals. The proposed method is advantageous because it does not require a huge amount of sampling data, and this technique is better than traditional strategies to select optimal features in the multi-domain feature space. The results reveal that the proposed method TL-LSTM can solve the problem of small sample training very well. Keywords Anti-cloning · Long short-term memory · Wireless transmission security · RF devices · Signal noise ratio · Transfer learning
1 Introduction With the development of mobile communication system equipment and the Internet of Things, wireless transmission technology plays an increasingly important role in modern society [29]. Compared with wired network, wireless networks bring more convenience to our daily life, and they greatly eliminate wiring and decoration costs. However, wireless signals are often used as the cornerstone of large-scale malicious attacks, and the broadcast nature of wireless transmissions often makes the problem worse. Intrusive attacks on electronic devices are growing rapidly, forcing us to pay
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Xueli Wang [email protected]
Extended author information available on the last page of the article
Circuits, Systems, and Signal Processing
more and more attention to security issues. Therefore, it is a necessary and rising research field to ensure the security of wireless information transmission. Physical layer security is the most basic part of wireless transmission security. Many attackers invade our systems by copying devices and analog signals. They replicate similar devices to gain unauthorized access, which greatly increases the insecurity of wireless communications. Therefore, combating RF device cloning is an urgent issue that we need to address. Fortunately, there are no two identical devices in the world, even if the two devices produced in succession are slightly different. The differences between devices are caused by device noise and hardware production errors, which would be reflected in their output signals. That gives us the
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