Research On Key Technology Of UAV Measurement And Control Network Security

With the rapid development of information technology and the increasing application of unmanned aerial vehicle(UAV)in various fields,the UAV measurement and control network is more and more seriously affected by noise interference,and due to some malicious damage from attackers,the UAV measurement and control network is facing serious security threats.When UAV measurement and control network is in the complex electromagnetic environment with more security threats,it is necessary to deploy a safe and reliable protection strategy to protect the data transmitted in the network,so as to effectively resist attacks from malicious nodes.Aiming at the security problem of UAV measurement and control network,this paper focuses on the research of UAV measurement and control network security protection strategy,using deep belief network to achieve intrusion detection of complex data streams,and designing a secure routing scheme suitable for UAV measurement and control network.Time-frequency analysis and convolutional neural network are used to realize the interference signal recognition of the measurement and control link.The main research contents of this paper include:(1)Analysis of security protection strategy based on UAV measurement and control network.In order to solve the problem of the safe transmission of UAV data in the complex network environment,this paper analyzes the security protection strategy of UAV measurement and control network.Firstly,the structure of UAV measurement and control network system is introduced,and its system composition,protocol stack architecture and communication terminal structure are studied.Then the common attack modes and security threat characteristics of UAV measurement and control network are described.Finally,the security protection strategy of UAV measurement and control network is constructed.This paper proposes intrusion detection technology based on active defense,secure routing technology based on mobile self-organizing networks and interference recognition technology of measurement and control link.Through the research of this paper,it provides a theoretical basis for the security protection of UAV measurement and control network.(2)Research on intrusion detection technology based on deep belief network.In order to solve the intrusion detection problem of massive,high-dimensional and nonlinear data in UAV measurement and control network,this paper applies the deep learning method of multi-layer nonlinear mapping to the intrusion detection of UAV measurement and control network,and proposes an intrusion detection model based on deep belief network.Aiming at the unbalanced distribution of categories in the intrusion detection dataset,synthetic minority oversampling technology is used for preprocessing.In the training process of network structure,the pre training algorithm based on contrast divergence is adopted,and the network weight is adjusted by using the error back propagation algorithm.Finally,the particle swarm optimization algorithm is used to optimize the super parameters of the model,so as to obtain the optimal deep belief network structure.Through the research of this paper,an effective solution is provided for the intrusion detection problem of UAV measurement and control network.(3)Research on secure routing technology based on cryptosystem.In order to solve the security problem of routing information in the UAV measurement and control network,this paper applies elliptic curve cryptography,one-way hash function and other technologies to the design of secure routing schemes,and proposes a secure routing scheme based on cryptosystems.This scheme overcomes the shortcomings of existing security routing schemes,and can better adapt to UAV measurement and control network,which is a security sensitive and resource constrained environment.Through the research of secure routing technology,it can effectively resist the attack of malicious nodes in UAV measurement and control network,and improve the security of the network.(4)Research on interference recognition technology based on time-frequency analysis and convolutional neural network.In order to solve the problem of interference signal recognition of the UAV measurement and control link in a complex environment,this paper carries out mathematical modeling and analysis of four typical interference signals,and characterizes the characteristics of the interference signal through the time-frequency domain distribution image of the interference signal law.And on this basis,the method of convolutional neural network is used to identify the interference signal.Aiming at the problem of anti-interference in the UAV measurement and control link,the anti-interference technology based on spread spectrum communication and the interference suppression algorithm based on FFT overlap transform are studied.Finally,the interference recognition algorithm proposed in this paper is verified on the platform of software defined radio.Through the research of this paper,it can effectively improve the ability of interference recognition of the UAV measurement and control link.