A Survey: Machine Learning Based Security Analytics Approaches and Applications of Blockchain in Network Security

Abstract

Contemporarily, two emerging techniques, blockchain, and machine learning are driving dramatic rapid growth in the field of network security. This paper describes a literature review of machine learning approaches for network security analytics and summarizes some applications of blockchain in the field of network security. We first illustrate three types of network security data, including network traffic, software binary, and security logs. Then we discuss the application of machine learning and deep learning approaches to analyze these data. We cover a broad array of attack types, including malware, spam, insider threats, network intrusions. We also summarize some applications and potential development direction of blockchain technology.