Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Lapina, Maria; Mary Anita, E.A.; Vechkanov, Alexey; Tokmakova, Marina; Lapin, Vitalii Title A name given to the resource A Software Package for Detecting Anomalies in User Authentication Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Proceedings of 2025 IEEE International Conference on Contemporary Computing and Communications, InC4 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/InC465408.2025.11256363" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/InC465408.2025.11256363</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105030339337?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105030339337?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Lapina M., North Caucasian Federal University, Faculty of Mathematics and Computer Science named after prof. N. I. Chervyakov, Stavropol, Russian Federation; Mary Anita E.A., Christ University, Depatament of Computer Science, Bangalore, India; Vechkanov A., North Caucasian Federal University, Faculty of Mathematics and Computer Science named after prof. N. I. Chervyakov, Stavropol, Russian Federation; Tokmakova M., North Caucasian Federal University, Faculty of Mathematics and Computer Science named after prof. N. I. Chervyakov, Stavropol, Russian Federation; Lapin V., North Caucasian Federal University, Faculty of Mathematics and Computer Science named after prof. N. I. Chervyakov, Stavropol, Russian Federation Description An account of the resource Anomaly detection is a very important tool for various applications such as intrusion detection, fraud, malfunction, system health monitoring and event detection in IoT devices. Recently, user authentication has become an extremely popular topic in information security research environments. The definition of user authentication is formulated as the process of verifying the identity declared by the user for a system object. Authentication is a method used to distinguish between true or false authentication requests. There are many methods used to authenticate a user that can identify valid users in protected resources. This article discusses various methods for analyzing abnormal user behavior in information systems, namely such methods as machine learning, neural networks, hybrid methods. Based on the analysis of system logs in the Astra Linux operating system, a software package has been developed to identify anomalies when trying to authenticate users. 2025 IEEE. Subject The topic of the resource Abnormal Behavior; Artificial Intelligence; Audit Log; Deep Learning; Machine Learning; Neural Networks Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833152118-9; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online