5 citations · 13 across the 13 of their papers we have counts for
14 papers
Quantum Key Distribution Secured Federated Learning for Channel Estimation and Radar Spectrum Sensing in 6G Networks
Ferhat Ozgur Catak, Murat Kuzlu, Jungwon Seo +1
This paper presents a federated learning framework secured by quantum key distribution (QKD) for wireless channel estimation and radar spectrum sensing in the next generation netwo…
Logit-Level Uncertainty Quantification in Vision-Language Models for Histopathology Image Analysis
Betul Yurdem, Ferhat Ozgur Catak, Murat Kuzlu +1
Vision-Language Models (VLMs) with their multimodal capabilities have demonstrated remarkable success in almost all domains, including education, transportation, healthcare, energy…
Comparative Analysis of Attention Mechanisms for Automatic Modulation Classification in Radio Frequency Signals
Ferhat Ozgur Catak, Murat Kuzlu, Umit Cali
Automatic Modulation Classification (AMC) is a critical component in cognitive radio systems and spectrum management applications. This study presents a comprehensive comparative a…
BERT4MIMO: A Foundation Model using BERT Architecture for Massive MIMO Channel State Information Prediction
Ferhat Ozgur Catak, Murat Kuzlu, Umit Cali
Massive MIMO (Multiple-Input Multiple-Output) is an advanced wireless communication technology, using a large number of antennas to improve the overall performance of the communica…
Improving Medical Diagnostics with Vision-Language Models: Convex Hull-Based Uncertainty Analysis
Ferhat Ozgur Catak, Murat Kuzlu, Taylor Patrick
In recent years, vision-language models (VLMs) have been applied to various fields, including healthcare, education, finance, and manufacturing, with remarkable performance. Howeve…
Neural Networks Meet Elliptic Curve Cryptography: A Novel Approach to Secure Communication
Mina Cecilie Wøien, Ferhat Ozgur Catak, Murat Kuzlu +1
In recent years, neural networks have been used to implement symmetric cryptographic functions for secure communications. Extending this domain, the proposed approach explores the…
Uncertainty Quantification in Large Language Models Through Convex Hull Analysis
Ferhat Ozgur Catak, Murat Kuzlu
Uncertainty quantification approaches have been more critical in large language models (LLMs), particularly high-risk applications requiring reliable outputs. However, traditional…
Uncertainty Aware Deep Learning Model for Secure and Trustworthy Channel Estimation in 5G Networks
Ferhat Ozgur Catak, Umit Cali, Murat Kuzlu +1
With the rise of intelligent applications, such as self-driving cars and augmented reality, the security and reliability of wireless communication systems have become increasingly…
Mitigating Attacks on Artificial Intelligence-based Spectrum Sensing for Cellular Network Signals
Ferhat Ozgur Catak, Murat Kuzlu, Salih Sarp +2
Cellular networks (LTE, 5G, and beyond) are dramatically growing with high demand from consumers and more promising than the other wireless networks with advanced telecommunication…
Defensive Distillation based Adversarial Attacks Mitigation Method for Channel Estimation using Deep Learning Models in Next-Generation Wireless Networks
Ferhat Ozgur Catak, Murat Kuzlu, Evren Catak +2
Future wireless networks (5G and beyond) are the vision of forthcoming cellular systems, connecting billions of devices and people together. In the last decades, cellular networks…
Homomorphic Encryption and Federated Learning based Privacy-Preserving CNN Training: COVID-19 Detection Use-Case
Febrianti Wibawa, Ferhat Ozgur Catak, Salih Sarp +2
Medical data is often highly sensitive in terms of data privacy and security concerns. Federated learning, one type of machine learning techniques, has been started to use for the…
The Adversarial Security Mitigations of mmWave Beamforming Prediction Models using Defensive Distillation and Adversarial Retraining
Murat Kuzlu, Ferhat Ozgur Catak, Umit Cali +2
The design of a security scheme for beamforming prediction is critical for next-generation wireless networks (5G, 6G, and beyond). However, there is no consensus about protecting t…
Analysis of False Data Injection Impact on AI based Solar Photovoltaic Power Generation Forecasting
S. Sarp, M. Kuzlu, U. Cali +2
The use of solar photovoltaics (PV) energy provides additional resources to the electric power grid. The downside of this integration is that the solar power supply is unreliable a…
Security Concerns on Machine Learning Solutions for 6G Networks in mmWave Beam Prediction
Ferhat Ozgur Catak, Evren Catak, Murat Kuzlu +2
6G -- sixth generation -- is the latest cellular technology currently under development for wireless communication systems. In recent years, machine learning algorithms have been a…