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Signatureless Anomalous Behavior Detection in Information Systems
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0001-6237-177X
National Technical University of Ukraine .
National Academy of Sciences of Ukraine.
National Academy of Sciences of Ukraine.
2023 (English)In: Cybernetics and Systems Analysis, ISSN 1060-0396, E-ISSN 1573-8337, Vol. 59, no 5, p. 772-783Article in journal (Refereed) Published
Abstract [en]

The early detection of cyber threats with cyber-attacks adapted to the nature of information systems is a crucial cybersecurity problem. This problem and the task of recognizing normal and abnormal states and behavior of various processes in information systems are closely related. An additional condition is often the absence of templates, signatures, or rules of normal behavior that would allow the use of existing statistical or other known data analysis methods. We analyze the existing and propose a new method for detecting abnormal behavior without using signatures based on the finite state machine (FSM) model and the Security Information and Events Management (SIEM) system. © 2023, Springer Science+Business Media, LLC, part of Springer Nature.

Place, publisher, year, edition, pages
Springer, 2023. Vol. 59, no 5, p. 772-783
Keywords [en]
anomaly detection, cybersecurity, finite state machine, SIEM, time-series, Information management, Information systems, Information use, Network security, Anomalous behavior, Behavior detection, Condition, Cyber security, Cyber threats, Cyber-attacks, Finite states machine, Security information and event managements, Times series
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:bth-25487DOI: 10.1007/s10559-023-00613-yISI: 001083315900004Scopus ID: 2-s2.0-85173226907OAI: oai:DiVA.org:bth-25487DiVA, id: diva2:1806401
Available from: 2023-10-20 Created: 2023-10-20 Last updated: 2023-11-08Bibliographically approved

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Tkach, Volodymyr

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