Towards Adaptive Big Data Cyber-attack Detection via Semantic Link Networks

Abstract

As a core mechanism for cybersecurity, the ability to detect cyber-attacks is increasingly critical nowadays. There have been many types of network intrusion detection approaches, such as flow-based and packet-based, targeting single attack and multistage attack detection. Each approach has its own advantages and disadvantages. In this paper, we design an organic combination of these types of efforts into one comprehensive system. Furthermore, to deal with increasing volumes of network traffic and improve full packet analysis efficiency, we employ Spark Streaming platform for parallel detection.