Although Internet technology brings invaluable benefits to all walks of life, the security of network and information is becoming more and more prominent. The leakage of personnel information caused by Internet security incidents causes irreparable harm and loss to individuals or enterprises. E-commerce is a virtual transaction mode based on Internet technology. Its security requirements for transactions are more stringent than those for traditional transaction modes. Traditional identity authentication technology can no longer meet its security needs. People urgently need a reliable identity authentication system, meaning to ensure the security of e-commerce. According to the actual application scenarios of the algorithm in e-commerce, this paper, based on the research on face recognition technology, focuses on the in-depth research on face detection technology under the background of big data in order to introduce face recognition technology in this paper. This paper proposes a feature-based face matching algorithm. The face image is preprocessed to improve the accuracy of real-time face detection and reduce the false detection rate. Based on the research of traditional facial feature extraction technology, a virtual sample set that can effectively support a traditional facial feature extraction algorithm is constructed to solve the problem of insufficient training samples in practical applications. The experimental results showed that the accuracy of the method in this paper can reach up to 79.5% and that the minimum time consumption is only 0.142 s. Compared with the traditional method, the accuracy rate is higher and the time consumption is shorter.

Healthy life has always been the goal pursued by human beings. Physical health is not just about physical health but also mental health. Although mental health has become more and more important in people’s minds, there are still a large number of people who do not understand psychological counseling or do not enjoy psychological counseling. Based on this, this paper was aimed at designing a mental health counseling service platform, so that most people can solve their own psychological problems through the modern high-speed developed network. For the design of the platform, this paper focuses on the design of three functions: instant messaging, psychological testing, and expert consultation. The optimization of the platform uses the genetic algorithm to optimize the wireless communication technology, so that the communication efficiency of the platform is higher and the energy consumption is less. The experimental results of this paper show that compared with the other three algorithms, the algorithm in this paper is in the leading position, and the overall power consumption is reduced by 10%. And after testing, the platform of this paper can operate effectively and can provide a solution platform for mental health counseling users.