CopAS: A Big Data Forensic Analytics System
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F23%3A00130487" target="_blank" >RIV/00216224:14330/23:00130487 - isvavai.cz</a>
Result on the web
<a href="https://www.scitepress.org/PublicationsDetail.aspx?ID=umluZcUjShA=&t=1" target="_blank" >https://www.scitepress.org/PublicationsDetail.aspx?ID=umluZcUjShA=&t=1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5220/0011929000003482" target="_blank" >10.5220/0011929000003482</a>
Alternative languages
Result language
angličtina
Original language name
CopAS: A Big Data Forensic Analytics System
Original language description
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.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF16_019%2F0000822" target="_blank" >EF16_019/0000822: CyberSecurity, CyberCrime and Critical Information Infrastructures Center of Excellence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 8th International Conference on Internet of Things, Big Data and Security IoTBDS - Volume 1
ISBN
9789897586439
ISSN
2184-4976
e-ISSN
—
Number of pages
12
Pages from-to
150-161
Publisher name
SciTePress
Place of publication
Setubal, Portugal
Event location
Prague, Czech Republic
Event date
Jan 1, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001078900300014