Data Legal Supervision of Online Car-Hailing Platform Based on Big Data Technology and Edge Computing

Abstract

There is a lack of fairness in market competition and disorder of order as a result of the lack of supervision. OCH (online car-hailing) driver accidents are also reported frequently, causing a slew of social and traffic safety issues. In this paper, we reconstruct the logical path of OCH platform data legal supervision in China's big data era. We propose a big data encryption algorithm based on data redundancy technology that combines the characteristics of the ECC (Elliptic Curve Cryptography) and AES (Advanced Encryption Standard) block cipher modes in terms of computing speed, parallelism, and security. The system can process large amounts of network data and detect distributed denial of service (DDOS) attacks in real time. The observed feature change trend charts before and after the attacks show significant differences, demonstrating that the proposed features can better distinguish normal traffic from abnormal traffic.