Title | Using CyberScore for Network Traffic Monitoring |
Publication Type | Conference Paper |
Year of Publication | 2022 |
Authors | Deri, Luca, Cardigliano, Alfredo |
Conference Name | 2022 IEEE International Conference on Cyber Security and Resilience (CSR) |
Date Published | jul |
Keywords | Computer crime, deep packet inspection, Industries, Inspection, Monitoring, network intrusion detection, open-source, pubcrawl, resilience, Resiliency, Scalability, Security Score, statistical analysis, telecommunication traffic, Traffic Measurement |
Abstract | The growing number of cybersecurity incidents and the always increasing complexity of cybersecurity attacks is forcing the industry and the research community to develop robust and effective methods to detect and respond to network attacks. Many tools are either built upon a large number of rules and signatures which only large third-party vendors can afford to create and maintain, or are based on complex artificial intelligence engines which, in most cases, still require personalization and fine-tuning using costly service contracts offered by the vendors.This paper introduces an open-source network traffic monitoring system based on the concept of cyberscore, a numerical value that represents how a network activity is considered relevant for spotting cybersecurity-related events. We describe how this technique has been applied in real-life networks and present the result of this evaluation. |
DOI | 10.1109/CSR54599.2022.9850289 |
Citation Key | deri_using_2022 |