Identification of network threats using live log stream analysis

The field of information security has covered various sectors in order to secure data which is stored online, offline, and during transmission over the network. The standard process of system log analysis is to first parse unstructured logs into structured data, and then apply data mining and machine learning techniques to analyze the data and build a threat detection model. This paper proposes a novel idea for identifying the network threat in an organisation. We take live network device logs in different log formats as input and send them for analysis. Whether a live log contains an anomaly, any vulnerability, or any insider threat will be identified. To find suspicious activity in the network, the logs will be processed, and find any activity at the same time.