CopAS: A Big Data Forensic Analytics System

D 2023

CopAS: A Big Data Forensic Analytics System

MACÁK, Martin, Tomáš REBOK, Matúš ŠTOVČIK, Mouzhi GE, Bruno ROSSI et. al.

Základní údaje

Originální název

CopAS: A Big Data Forensic Analytics System

Autoři

MACÁK, Martin (703 Slovensko, garant, domácí), Tomáš REBOK (203 Česká republika, domácí), Matúš ŠTOVČIK (703 Slovensko, domácí), Mouzhi GE (156 Čína), Bruno ROSSI (380 Itálie, domácí) a Barbora BÜHNOVÁ (203 Česká republika, domácí)

Vydání

Setubal, Portugal, Proceedings of the 8th International Conference on Internet of Things, Big Data and Security IoTBDS - Volume 1, od s. 150-161, 12 s. 2023

Nakladatel

SciTePress

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Portugalsko

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

elektronická verze "online"

Odkazy

URL

Kód RIV

RIV/00216224:14330/23:00130487

Organizační jednotka

Fakulta informatiky

ISBN

978-989-758-643-9

ISSN

DOI

http://dx.doi.org/10.5220/0011929000003482

UT WoS

001078900300014

Klíčová slova anglicky

Network Security; Network Traffic Analysis; Forensics Analysis; Big Data; Insider Attack Detection

Štítky

firank_B

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 7. 4. 2024 22:54, RNDr. Pavel Šmerk, Ph.D.

Anotace

V originále

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.

Návaznosti

CZ.02.1.01/0.0/0.0/16_019/0000822, interní kód MU
(Kód CEP: EF16_019/0000822)

Název: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur (Akronym: C4e)

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur, PO 1 Posilování kapacit pro kvalitní výzkum

EF16_019/0000822, projekt VaV

Název: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur

Citovat

MACÁK, Martin, Tomáš REBOK, Matúš ŠTOVČIK, Mouzhi GE, Bruno ROSSI a Barbora BÜHNOVÁ. CopAS: A Big Data Forensic Analytics System. Online. In Proceedings of the 8th International Conference on Internet of Things, Big Data and Security IoTBDS - Volume 1. Setubal, Portugal: SciTePress, 2023, s. 150-161. ISBN 978-989-758-643-9. Dostupné z: https://dx.doi.org/10.5220/0011929000003482.

@inproceedings{2269259,
   author = {Macák, Martin and Rebok, Tomáš and Štovčik, Matúš and Ge, Mouzhi and Rossi, Bruno and Bühnová, Barbora},
   address = {Setubal, Portugal},
   booktitle = {Proceedings of the 8th International Conference on Internet of Things, Big Data and Security IoTBDS - Volume 1},
   doi = {http://dx.doi.org/10.5220/0011929000003482},
   keywords = {Network Security; Network Traffic Analysis; Forensics Analysis; Big Data; Insider Attack Detection},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Setubal, Portugal},
   isbn = {978-989-758-643-9},
   pages = {150-161},
   publisher = {SciTePress},
   title = {CopAS: A Big Data Forensic Analytics System},
   url = {https://www.scitepress.org/PublicationsDetail.aspx?ID=umluZcUjShA=&t=1},
   year = {2023}
}

TY  - JOUR
ID  - 2269259
AU  - Macák, Martin - Rebok, Tomáš - Štovčik, Matúš - Ge, Mouzhi - Rossi, Bruno - Bühnová, Barbora
PY  - 2023
TI  - CopAS: A Big Data Forensic Analytics System
PB  - SciTePress
CY  - Setubal, Portugal
SN  - 9789897586439
KW  - Network Security
KW  - Network Traffic Analysis
KW  - Forensics Analysis
KW  - Big Data
KW  - Insider Attack Detection
UR  - https://www.scitepress.org/PublicationsDetail.aspx?ID=umluZcUjShA=&t=1
N2  - 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.
ER  -

MACÁK, Martin, Tomáš REBOK, Matúš ŠTOVČIK, Mouzhi GE, Bruno ROSSI a Barbora BÜHNOVÁ. CopAS: A Big Data Forensic Analytics System. Online. In \textit{Proceedings of the 8th International Conference on Internet of Things, Big Data and Security IoTBDS - Volume 1}. Setubal, Portugal: SciTePress, 2023, s.~150-161. ISBN~978-989-758-643-9. Dostupné z: https://dx.doi.org/10.5220/0011929000003482.

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