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 threat 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 networking data streams generated during the daily activities of an organization.
翻译:随着社会数字化的推进,网络安全已成为大多数组织的主要关切之一。本文介绍CopAS,这是一个旨在进行大数据法证分析的系统,使网络操作者能够舒适地分析大量网络数据并将其联系起来,以了解潜在的恶意和可疑事件。我们展示了CopAS在公开提供的PCAP数据集中用于内部威胁探测的实际用途,并展示了如何利用该系统在组织日常活动中产生的大量网络数据流中发现内部人员隐藏其恶意活动。