With the advancing digitization of our society, network security has become one of the critical concerns for most organizations. In this paper, we present CopAS, a system targeted at Big Data forensics analysis, allowing network operators to comfortably analyze and correlate large amounts of network data to get insights about potentially malicious and suspicious events. We demonstrate the practical usage of CopAS for insider attack detection on a publicly available PCAP dataset and show how the system can be used to detect insiders hiding their malicious activity in the large amounts of data streams generated during the operations of an organization within the network.
@article{arxiv.2212.04843,
title = {CopAS: A Big Data Forensic Analytics System},
author = {Martin Macak and Matus Stovcik and Tomas Rebok and Mouzhi Ge and Bruno Rossi and Barbora Buhnova},
journal= {arXiv preprint arXiv:2212.04843},
year = {2023}
}