Signatureless Anomalous Behavior Detection in Information Systems
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-25487 DOI: 10.1007/s10559-023-00613-y ISI: 001083315900004 Scopus ID: 2-s2.0-85173226907 OAI: oai:DiVA.org:bth-25487 DiVA, id: diva2:1806401
2023-10-202023-10-202023-11-08 Bibliographically approved