## 2 Related Works  
MEC can provide mobile users with a variety of services, including storage, computing, and data transmission. However, when sending data using an open wireless network, there will be a denial of service (DoS), interference, eavesdropping, data leakage, and other security issues. To address these issues, researchers have proposed a variety of solutions. For instance, in [8], the authors proposed an edge computing data protection model, enabling edge devices in other regions to share and securely access the resources. However, the computational complexity is higher in the proposed method. [PERSON] et al. [9] suggested an access tree design and attribute-based signature technology to achieve ciphertext updating and computing outsourcing in MEC. Nevertheless, there are still security vulnerabilities, and attackers can effortlessly impersonate legitimate mobile users or edge nodes. [PERSON] et al. [10] proposed an encrypted key exchange (EKE) protocol that combined the CP-ABE method and digital signature technology to achieve security goals such as identity verification, confidentiality, and access control. Similarly, [PERSON] et al. [11; 12] investigated a defense architecture including an edge layer to preclude DoS attacks between mobile users and cloud computing, improving network performance. However, the authors fail to consider the security threat between mobile users and the edge layer. Artificial intelligence technology can adapt to attack detection in dynamic unknown environments by using current perceptual information for trial-and-error learning. The detection method based on reinforcement learning algorithms can obtain higher detection performances in an unknown communication environment, so it is more suitable for the development of future wireless communication. [PERSON] et al. [13] proposed a physical layer authentication method based on a machine learning and channel-based scheme. Only in specific industrial scenarios can the scheme show strong security and low computing energy consumption. [PERSON] et al. [14] comprehensively introduced the technologies and theories related to physical layer authentication in wireless communication. In various wireless systems, malicious users pose security threats to other users through disguised attacks. He pointed out that wireless communication leads to more security vulnerabilities due to its open nature and put forward some suggestions for current wireless systems. There are two main types of physical-layer-oriented authentication technologies. The first is to embed the identity information into the transmission signal, through the identity information for authentication [15; 16; 17]. Another type of approach is to take advantage of physical layer properties inherent in wireless transport for device authentication [18; 19]. General wireless security schemes generally rely on encryption algorithms and protocol layer authentication, but there is no feasible scheme for security threats of physical layer vulnerabilities and interfaces. Therefore, [PERSON] et al. [19] used the time-varying carrier frequency offset feature in the physical layer authentication process, and designed an adaptive device identification method. The physical layer key generation (PKG) method can generate a key having characteristics of reciprocity, uniqueness, and randomness of channel state information (CSI). Both the transmitter and receiver use a common key to send and receive information. The works in [20; 21; 22; 23] presented a key PKG method, which is an important research content in wireless system security, achieving secure communication. For instance, [PERSON] et al. proposed a secret key generation (SKG) scheme in [24], which can prevent man-in-the-middle (MITM) attacks by encrypting and authenticating the wireless channel. [PERSON] et al. [25] proposed an effective channel information extraction algorithm to avoid interference and noise that could reduce the key disagreement rate (KDR), achieving the goal of improving SKG. [PERSON] et al.