Visible to the public From Data-Driven to Intelligent-Driven: Technology Evolution of Network Security in Big Data Era

TitleFrom Data-Driven to Intelligent-Driven: Technology Evolution of Network Security in Big Data Era
Publication TypeConference Paper
Year of Publication2019
AuthorsZhu, Yan, Zhang, Yi, Wang, Jing, Song, Weijing, Chu, Cheng-Chung, Liu, Guowei
Conference Name2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC)
KeywordsAccess Control, authentication, authorisation, Big Data, big data era, big data security technologies, Communication networks, compositionality, computer network security, cryptography, data encryption, data privacy, disaster recovery, DT security principles, encryption audits, Human Behavior, Identification, Information systems, information technology, Intelligent Data and Security, Intelligent Data Security, intrusion prevention, network security technology, Organizations, Predictive Metrics, pubcrawl, Resiliency, Scalability, security, security assurance strategy, security audit, Security Audits, security category, security principles, security technology evolution, Standards organizations, System recovery, system virtualization

With the advent of the big data era, information systems have exhibited some new features, including boundary obfuscation, system virtualization, unstructured and diversification of data types, and low coupling among function and data. These features not only lead to a big difference between big data technology (DT) and information technology (IT), but also promote the upgrading and evolution of network security technology. In response to these changes, in this paper we compare the characteristics between IT era and DT era, and then propose four DT security principles: privacy, integrity, traceability, and controllability, as well as active and dynamic defense strategy based on "propagation prediction, audit prediction, dynamic management and control". We further discuss the security challenges faced by DT and the corresponding assurance strategies. On this basis, the big data security technologies can be divided into four levels: elimination, continuation, improvement, and innovation. These technologies are analyzed, combed and explained according to six categories: access control, identification and authentication, data encryption, data privacy, intrusion prevention, security audit and disaster recovery. The results will support the evolution of security technologies in the DT era, the construction of big data platforms, the designation of security assurance strategies, and security technology choices suitable for big data.

Citation Keyzhu_data-driven_2019