Dr. Areeb Ahmed, a postdoctoral researcher under the SMASH programme, presented his paper "Configuring KNN-based Receiver for Machine Learning-assisted Secure Random Communication System under Gaussian Environment" at the IEEE 17th International Conference on Electronics, Computers and Artificial Intelligence (ECAI 2025). The work, co-authored with prof. dr. Zoran Bosnić, was presented at Valahia University of Targoviste, Romania.

Physical Layer Security (PLS) is considered the boundary wall of modern communication systems. The paper introduces a novel covert communication approach by integrating machine learning with random communication systems to encrypt and decrypt binary information using alpha-stable noise signals. It presents the first known configuration of an architecture that applies machine learning for the encryption of alpha-stable noise signals.

The results demonstrate that the Machine Learning-assisted Secure Random Communication System is resistant to eavesdropping under all AWGN channel environments, making it a strong candidate for establishing secure communication in future 5G and 6G technologies.