First, the essential characteristics of large-scale, real-time and distributed processing of big data (making the solution of big data exceed the data management and processing requirements of previous data management systems, for example, in terms of capacity, real-time, distributed architecture and parallel processing).
This makes it more difficult to ensure the security of these systems. Big data cluster is open and self-organizing, which supports users to communicate with multiple data nodes at the same time.
Second, embedded security: In the crazy competition involving big data, most development resources are used to improve the scalability, usability and analysis function of big data. Only a few functions are used to add security functions.
However, you want to embed security features in the big data platform. You want developers to support the required functionality during the design and deployment phases. You want security features to be as scalable, high-performance and self-organizing as big data clusters.
Third, applications: Most applications of big data clusters are web applications, which utilize Web-based technologies and stateless REST-based APIs. Web-based applications and APIs pose one of the biggest threats to these big data clusters. After being attacked or destroyed.
They can provide unrestricted access to data stored in big data clusters. Application security, user access management and authorization control are very important, and they are as indispensable as security measures focused on ensuring the security of big data clusters.