activity
20212023
most citedThe Adversarial Security Mitigations of mmWave Beamforming Prediction Models using Defensive Distillation and Adversarial Retraining

2 citations · 4 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CR2023

5G-SRNG: 5G Spectrogram-based Random Number Generation for Devices with Low Entropy Sources

Ferhat Ozgur Catak, Evren Catak, Ogerta Elezaj

Random number generation (RNG) is a crucial element in security protocols, and its performance and reliability are critical for the safety and integrity of digital systems. This is…

cs.NI2022

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…

cs.CR2022★ 1 cited

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…

cs.CR2022★ 2 cited

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…

eess.SP2021

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…

cs.LG2021★ 1 cited

Adversarial Machine Learning Security Problems for 6G: mmWave Beam Prediction Use-Case

Evren Catak, Ferhat Ozgur Catak, Arild Moldsvor

6G is the next generation for the communication systems. In recent years, machine learning algorithms have been applied widely in various fields such as health, transportation, and…