Akademik Veri Yönetim Sistemi
Kara A. (Yürütücü), Karakaya M.
Yükseköğretim Kurumları Destekli Proje, BAP Araştırma Projesi, 2025 - 2027
In next-generation networks, Radio Frequency Fingerprinting (RFF) technologies are anticipated to play a significant role in network security, specifically in the access and authorization process. Recently, the integration of Artificial Intelligence (AI) and Deep Learning (DL) into RFF systems has become widespread and is preferred due to its reliability. DL-supported RFF solutions have made great progress in terms of classification accuracy, which is critical for device network access.
The primary objective of this project is to model the aging of radio device transmitter hardware in next-generation networks and subsequently use this model to develop a sustainable and scalable RFF system. The project coordinator has prior experience in similar areas, with developments from their students' theses and other projects related to DL-supported RFF solutions, and this expertise will be further developed and applied here. The researcher's physics background will provide support for the physical modeling dimension of aging in oscillator-based components.