Публікація:
Access Control to Robotic Systems Based on Biometric: The Generalized Model and its Practical Implementation

dc.contributor.authorAbu-Jassar Amer Tahseen
dc.contributor.authorAttar Hani
dc.contributor.authorLyashenko, V.
dc.contributor.authorAmer Ayman
dc.contributor.authorSotnik, S.
dc.contributor.authorSolyman Ahmed
dc.date.accessioned2023-08-27T09:05:44Z
dc.date.available2023-08-27T09:05:44Z
dc.date.issued2023
dc.description.abstractThe paper presents a generalized system's structural scheme and components for monitoring and controlling access to robotic systems based on biometric data for decision-making. Mathematical decision-making models for choosing the best alternative based on fuzzy sets are proposed. The fuzzy analytical hierarchy process determined weights of 6 criteria (for k1 criterion weighting factor is equal to 2.2; for k2 criterion – 1.8; for k3 criterion – 0.6; for k4 criterion – 0.6; for k5 criterion – 0.6; for k6 criterion – 0.2, that is, most weighty would be k1 – recognition accuracy) against which the best option was evaluated. Thus, during evaluation of alternative on six criteria it was obtained that t alternative X1 (face recognition in full-face), will have the key value of embership function of resulting fuzzy set alternatives with ideal value of integral criterion, equal to 0.53, and as result, implemented rational choice, taking into account given criteria. The difference is that we have introduced such criteria as anti-spoofing. The access control system for robotic systems works in real-time. It is implemented based on an algorithmic decision -making complex, which includes two-factor authentication to increase security: registration involves entering emp loyee data from the keyboard (password, login, surname, first name, position) and physiological uthentication (identification by face). Face detection is proposed to be implemented on several images: face, profile, face, and profile in the mask. A distinctive feature of our development is that often, a main requirement for "access control systems with facial identification" is the frontal location of the face relative to the camera; in our case, the image of the face at an angle was added.
dc.identifier.citationAbu-Jassar A. T., Attar H., Lyashenko V, Amer A., Sotnik S, & Solyman A. (2023). Access Control to Robotic Systems Based on Biometric: The Generalized Model and its Practical Implementation. International Journal of Intelligent Engineering and Systems, 16(5), 313-328.
dc.identifier.issn2185-310X
dc.identifier.urihttps://openarchive.nure.ua/handle/document/23984
dc.language.isoen
dc.publisherINASS
dc.subjectRobotic systems
dc.subjectBiometric data
dc.titleAccess Control to Robotic Systems Based on Biometric: The Generalized Model and its Practical Implementation
dc.typeArticle
dspace.entity.typePublication

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