# On Improving 5G Internet of Radio Light Security Based on LED Fingerprint Identification Method
## 1 Introduction  
With the enormous growth of wireless devices and the deep integration of information technology into a number of industrial applications [1], the 5G network is expected to support massive user connections and exponentially increase wireless services. In addition, due to a tremendous number of Internet-of-Things (IoT) devices featured by the massive Machine-Type Communication (mMTC) extensive applications in the 5G network, high data rates, high connection density and ultra-reliable low latency communication (URLLC) should be provided. Moreover, security must be urgently assured by the future 5G network [2]. Hence, traditional radio frequency (RF) networks, which are already crowded, are are arduous to satisfy these high demands [3]. One of the new communication technologies that has been proposed as an auspicious solution for the 5G and beyond is Visible Light Communication (VLC) [4]. VLC provides the nomadic access in hundreds of terahertz (THz) of unlicensed optical spectrum, immunity to electromagnetic interference, safety and security, simple implementation, and deployment of systems [5; 6; 7]. These exciting assets generate considerable research and industrial interests for the indoor VLC, especially with the approval of the IEEE 802.15.7 standard [8]. The research in this topic is conducted in the European H2020 project Internet of Radio Light (IoRL), which was the first to propose a hybrid indoor optical-radio network in convergence with the 5G Era [9; 10; 11]. The advantage of the VLC compared to radio [4] and its applications scenarios [12; 13] has been widely discussed in the VLC literature. Due to the line-of-sight light propagation and the impermeability for non-transparent objects, the VLC channel exhibits higher security in a single-user or private-room scenario. However, in public areas such as classrooms, libraries, hallways, or planes, the security of the transmitted signal cannot be guaranteed [14]. Device fingerprinting, the process of gathering device information to generate device-specific signatures and using them to identify individual devices, has emerged as a potential solution for the 5G network to reduce the vulnerability of wireless networks to node forgery or insider attacks [15; 16]. Its low-complexity and difficult or impossible to forge property could be perfectly matched with the security requirements of the 5G network. Notably, wireless device identification via Radio Frequency (RF) fingerprint becomes a widely concerned physical-layer security mechanism [17] and has been investigated in Wi-Fi, LTE (Long Term Evolution) and ZigBee systems. It provides an opportunity to accomplish the authentication and the target device identification in the physical layer. Recently, a RF fingerprint-based device identification method successfully demonstrated 92.29% identification accuracy on a set of seven 2.4 GHz commercial ZigBee devices [18]. It must be noted that device fingerprinting schemes can also be applied in the same spirit to VLC systems. However, the distinctive transmission protocols and modulation schemes of VLC systems such as intensity-modulation direct detection (IM/DD), direct-current (DC) biased optical orthogonal frequency-division multiplexing (DCO-OFDM) [19] necessitate the development of new device fingerprinting methods specific to VLC systems [20]. Currently, little research on VLC device identification exists. However, drawing on lessons from the successful implementations of device identification via RF fingerprint provides the possibility to propose the appropriate and efficient device identification method also for VLC systems. The concept of RF fingerprinting was firstly proposed by [PERSON] et al. in 2003 [21]. This device identification method is featured by the detection of the transient signal emitted by the transmitter. [PERSON] et al. was the first to introduce the device identification method based on the steady-state signal [22].