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The BP neural network model is a hot issue in recent academic research, and it has been successfully applied to many other fields, but few researchers apply the BP neural network model to the field of automobile insurance. The main method that has been used in the prediction of the total claim amount in automobile insurance is the generalized linear model, where the BP neural network model could provide a different approach to estimate the total claim loss. This paper uses a genetic algorithm to optimize the structure of the BP neural network at first, and the calculation speed is significantly improved. At the same time, by considering the overfitting problem, an early stop method is introduced to avoid the overfitting problem. In the model, a three-layer BP neural network model, which includes the input layer, hidden layer, and output layer, is trained. With consideration of various factors, a total claim amount prediction model is established, and the trained BP neural network model is used to predict the total claim amount of automobile insurance based on the data of the training set. The results show that the accuracy of the prediction by using the BP neural network model to both the data of Shandong Province and to the data of six cities is over 95%. Then, the predicted total claim amount is used to calculate premiums for five cities in Shandong Province according to credibility theory. The results show that the average premium of the five cities is slightly higher than the actual claim amount of the city. The combination of BP neural network and credibility theory can perform accurate claim amount estimation and pricing for automobile insurance, which can effectively improve the current situation of the automobile insurance business and promote the development of insurance industry.

This paper investigates secure transmission in unmanned aerial vehicle (UAV) relay-assisted millimeter wave (mmWave) networks, where the selected UAV relay performs secure transmission in both the on-off and non-on-off schemes. Meanwhile, there are multiple eavesdroppers randomly distributed on the ground and attempting to wiretap the transmission. Leveraging the air-to-ground channel model and the tools of stochastic geometry, the novel expressions of transmit probability (TP) and secrecy outage probability (SOP) are derived in both the on-off and non-on-off transmission schemes with perfect beam alignment. The secrecy performance improvement is demonstrated in the on-off transmission scheme, and we find that there exists an optimal altitude of UAV relays to achieve the best TP. In addition, due to the limitations of UAV carriers, such as its low computational capacity and high mobility, the perfect beam alignment is difficult to achieve in the mmWave networks aided by UAV relays, and the effect of beam alignment error on the secrecy performance is investigated in the considered networks. Analyzing the numerical and simulation results, we find that the SOP will not have obvious deterioration when the beam alignment error is relatively small, and the SOP can be improved by using the antennas with a large number of elements. However, in high beam alignment error regime, the antenna arrays with a smaller number of elements will provide the better SOP.

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Fine-grained spectrum management is promising in addressing the contradiction between the access requirements for massive radio systems and the shortage of spectrum resources. It is difficult to identify the radio system and securely transmit its spectrum identity information due to the complexity, openness, and variability of the electromagnetic environment, which has become a major challenge for the fine-grained spectrum management. In this paper, we consider a practical and proactive spectrum monitoring scenario, where the spectrum monitoring node monitors the communication signal sent by a source node to a destination node for the fine-grained spectrum management. A malicious node eavesdrops on the transmission for accessing and deceiving them. We propose a secure transmission method of spectrum watermark for the fine-grained spectrum management. The spectrum watermark for identifying the radio system is hidden in the normal communication signal via adjusting the embedding parameters, and has no effect on the required transmission performance. We investigate the transmission performance of the spectrum watermark in two typical use cases. In first case, the transmission rate of the communication signal is given and fixed. In another case, the transmission rate of the communication signal can be adaptively adjusted according to the channel quality. The analysis and simulation results show that the proposed method achieves the optimal and secure transmission of the spectrum watermark by adjusting the embedding parameters of the spectrum watermark while ensuring the required and optimal transmission performance of the communication signal. INDEX TERMS Fine-grained spectrum management, spectrum watermark, embedding parameters of spectrum watermark, secure transmission. I. INTRODUCTION With the rapid development and broad application of wireless communication technology, the number of mobile users and their requirements for bandwidth are growing rapidly. According to Cisco's 2019 visual network index, global mobile data traffic would grow 7-fold from 2017 to 2022 [1]. The shortage of spectrum resources has become a bottleneck The associate editor coordinating the review of this manuscript and approving it for publication was Ruofei Ma. restricting the sustainable development and application of wireless communication technology. Fine-grained spectrum management, which can improve the effectiveness of spectrum management, is regarded as one of the most promising methods to solve the contradiction between the increasing spectrum demand and the shortage of spectrum resources. Radio spectrum identification is critical to achieve the fine-grained spectrum management. Due to the openness of the electromagnetic environment and the boundless of wireless transmission, the spectrum identification information of

Information hiding is an important technique for information security, which is wildly studied by researchers. Recently embedding methods are proposed in spatial, frequency and other domains. After investigating previous literatures, we find that there is still room for embedding performance improvement. Inspired by some literatures, we propose a new method (Modulus Calculations on Prime Number Algorithm, MOPNA) for embedding secret data into cover-images. The main idea of MOPNA is hiding confidential data in paired cover-pixels with modulus calculation based on weight parameters consisting of prime numbers. MOPNA improves the embedding capacity while maintaining good stego-image quality. The correctness of MOPNA method is proved by a combination of mathematical and programming proof. The experimental results prove that the proposed method has high embedding capacity and achieves better comprehensive performance than existing methods.