MACÁK, Martin, Radek OŠLEJŠEK and Barbora BÜHNOVÁ. Detecting Masquerading Traitors from Process Visualization of Computer. Online. In 2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). Neuveden: IEEE, 2023, p. 1935-1940. ISBN 979-8-3503-8200-6. Available from: https://dx.doi.org/10.1109/TrustCom60117.2023.00263.
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Basic information
Original name Detecting Masquerading Traitors from Process Visualization of Computer
Authors MACÁK, Martin (703 Slovakia, guarantor, belonging to the institution), Radek OŠLEJŠEK (203 Czech Republic, belonging to the institution) and Barbora BÜHNOVÁ (203 Czech Republic, belonging to the institution).
Edition Neuveden, 2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), p. 1935-1940, 6 pp. 2023.
Publisher IEEE
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Confidentiality degree is not subject to a state or trade secret
Publication form electronic version available online
WWW URL
Organization unit Faculty of Informatics
ISBN 979-8-3503-8200-6
Doi http://dx.doi.org/10.1109/TrustCom60117.2023.00263
Keywords in English insider attack;process visualization;cybersecurity;traitor;organization
Tags International impact, Reviewed
Changed by Changed by: doc. Ing. RNDr. Barbora Bühnová, Ph.D., učo 39394. Changed: 29/6/2024 19:29.
Abstract
Insider attacks in organizations are currently one of the most crucial cybersecurity challenges. Traitors are one of the most dangerous types of insider attackers. They are difficult to detect because they know the organization, processes, defense mechanisms, and employees. Besides abusing their rights and accesses, they can use their co-workers’ rights and accesses. They can hide their activities to perform attacks inconspicuously. The current masquerader detection techniques usually rely on the fact that the masquerader is an outsider, making them unable to detect attacks from the traitor. To detect these insider attackers, which we call masquerading traitors, we propose the human-as-solution approach and engage the employees in deciding whether the usage of their rights and accesses is suspicious and, therefore, might be performed by a masquerading traitor.
Links
MUNI/G/1142/2022, interní kód MUName: Forensic Support for Building Trust in Smart Software Ecosystems
Investor: Masaryk University, Forensic Support for Building Trust in Smart Software Ecosystems, INTERDISCIPLINARY - Interdisciplinary research projects
PrintDisplayed: 24/7/2024 23:28