Security Analysis of Intelligent System Based on Edge Computing

Abstract

At present, artificial intelligence technology is widely used in society, and various intelligent systems emerge as the times require. Due to the uniqueness of biometrics, most intelligent systems use biometric-based recognition technology, among which face recognition is the most widely used. To improve the security of intelligent system, this paper proposes a face authentication system based on edge computing and innovatively extracts the features of face image by convolution neural network, verifies the face by cosine similarity, and introduces a user privacy protection scheme based on secure nearest neighbor algorithm and secret sharing homomorphism technology. The results show that when the threshold is 0.51, the correct rate of face verification reaches 92.46%, which is far higher than the recognition strength of human eyes. In face recognition time consumption and recognition accuracy, the encryption scheme is basically consistent with the recognition time consumption in plaintext state. It can be seen that the security of the intelligent system with this scheme can be significantly improved. This research provides a certain reference value for the research on the ways to improve the security of intelligent system.