CopAS: A Big Data Forensic Analytics System

Logo poskytovatele

Varování

Publikace nespadá pod Filozofickou fakultu, ale pod Fakultu informatiky. Oficiální stránka publikace je na webu muni.cz.
Autoři

MACÁK Martin REBOK Tomáš ŠTOVČIK Matúš GE Mouzhi ROSSI Bruno BÜHNOVÁ Barbora

Rok publikování 2023
Druh Článek ve sborníku
Konference Proceedings of the 8th International Conference on Internet of Things, Big Data and Security IoTBDS - Volume 1
Fakulta / Pracoviště MU

Fakulta informatiky

Citace
www https://www.scitepress.org/PublicationsDetail.aspx?ID=umluZcUjShA=&t=1
Doi http://dx.doi.org/10.5220/0011929000003482
Klíčová slova Network Security; Network Traffic Analysis; Forensics Analysis; Big Data; Insider Attack Detection
Popis 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.
Související projekty:

Používáte starou verzi internetového prohlížeče. Doporučujeme aktualizovat Váš prohlížeč na nejnovější verzi.