State Tracking and Evaluation Technology for Big Data Objects Based on a New Digital Watermarking Algorithm
Jianfeng Deng, Nishui Cai · 2023
Currently, enterprises generally face the following problems in managing big data: Multiple versions or replicas of the same data object cross-system interfaces, delayed data destruction with invalid data not being cleared in time, difficulty in tracking data with no support of data traceability technology, weak data security and insufficient risk analysis capabilities. To address these problems, this article proposes a new digital watermarking algorithm that is suitable for embedding digital watermarks in big data objects. Combined with flow data analysis technology, it can track and monitor the processes of generating, storing, transmitting, processing, and publishing big data objects, mark the version status of data objects, draw the distribution map of enterprise data status, we innovatively apply this recognition technology to calculate key indicators such as the health value of big data object references and the number of invalid data object references, and analyze data objects using predefined weaknesses and risk rules to discover data security issues and provide danger warnings for enterprises.