Big Data Analytics of Network Traffic and Attacks

Big Data analytics for intrusion detection is an important topic in cybersecurity. Network flows and system events generate big data, which often leads to challenges in intrusion detection with high efficiency and good accuracy. This paper focuses on the `Variety' and `Veracity' of big data characteristics in network traffic and attacks. Datasets with various data types are analyzed; data duplicates removal and missing values detection are performed. A clustering analysis based on k-means are also conducted.