Investigation of E-Commerce Security and Data Platform Based on the Era of Big Data of the Internet of Things

Abstract

The Internet of Things (IoT) can combine a wide range of information space with physical space and use related technologies to provide effective information interaction between objects. Nowadays, a large amount of Internet data transmitted by E-commerce communication data is vulnerable to interference, intrusion, and other attacks, posing a major threat and challenge to data security. Based on the IoT data analysis platform Hadoop, starting from the data, the problems faced by the E-commerce information security are analyzed and the E-commerce security is improved. Through the comparison of Delphi method, fuzzy comprehensive evaluation method, weighted linear evaluation method, grey cluster analysis method, analytic hierarchy process, and using the complex fuzzy evaluation method of the vague set theory, the security weights of the first and second levels are calculated according to the vague entropy value of each index attribute. It provides a useful reference for E-commerce informatization security evaluation methods. The first-level and second-level comprehensive evaluations of the vague set are used to detect and analyze E-commerce network security, transaction security, data security, and physical security. The weight of each indicator occupies a total of 100% and the final risk status is close to 0. Therefore, it can be concluded that the risk status of the E-commerce information security is “safe”.