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Authors: Martin Macak 1 ; Tomas Rebok 2 ; Matus Stovcik 1 ; Mouzhi Ge 3 ; Bruno Rossi 1 and Barbora Buhnova 1

Affiliations: 1 Faculty of Informatics, Masaryk University, Brno, Czech Republic ; 2 Institute of Computer Science, Brno, Czech Republic ; 3 Deggendorf Institute of Technology, Deggendorf, Germany

Keyword(s): Network Security, Network Traffic Analysis, Forensics Analysis, Big Data, Insider Attack Detection.

Abstract: 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.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Macak, M.; Rebok, T.; Stovcik, M.; Ge, M.; Rossi, B. and Buhnova, B. (2023). CopAS: A Big Data Forensic Analytics System. In Proceedings of the 8th International Conference on Internet of Things, Big Data and Security - IoTBDS; ISBN 978-989-758-643-9; ISSN 2184-4976, SciTePress, pages 150-161. DOI: 10.5220/0011929000003482

@conference{iotbds23,
author={Martin Macak. and Tomas Rebok. and Matus Stovcik. and Mouzhi Ge. and Bruno Rossi. and Barbora Buhnova.},
title={CopAS: A Big Data Forensic Analytics System},
booktitle={Proceedings of the 8th International Conference on Internet of Things, Big Data and Security - IoTBDS},
year={2023},
pages={150-161},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011929000003482},
isbn={978-989-758-643-9},
issn={2184-4976},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Internet of Things, Big Data and Security - IoTBDS
TI - CopAS: A Big Data Forensic Analytics System
SN - 978-989-758-643-9
IS - 2184-4976
AU - Macak, M.
AU - Rebok, T.
AU - Stovcik, M.
AU - Ge, M.
AU - Rossi, B.
AU - Buhnova, B.
PY - 2023
SP - 150
EP - 161
DO - 10.5220/0011929000003482
PB - SciTePress

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