Corpus-Based Japanese Reading Teaching Database Cloud Service Model

With the widespread application of mobile Internet technology, big data, and artificial intelligence, the demand for computing resources in the whole society is growing rapidly. Database cloud service is an online managed high-availability database service built on a cloud computing platform. It can be used as a basic service of the cloud computing platform and has the characteristics of high service availability and high data reliability. The purpose of this paper is to design a corpus-based Japanese reading teaching database cloud service system and integrate a machine learning-based Structure Query Language (SQL) injection detection function for the system. The proposed work is as follows: (1) Design the basic framework of database cloud service. The module of cloud database service is introduced, and the realization logic of main system functions is analyzed. (2) A SQL injection classifier based on feature engineering and machine learning is designed for database cloud services, which can determine whether the input SQL command is an injection statement. The classifier is deployed between the database instance and the front-end server to integrate the SQL injection detection function into the cloud database instance. Then use the support vector machine algorithm to perform simulation experiments on the classifier model to compare the classification performance of the support vector machine algorithm when using different kernel functions. It is found that when the classification decision threshold is 0.5, the classifier using linear kernel function or radial basis kernel function has better classification performance for SQL sentences.