ADAPTIVE INTERFERENCE SUPPRESSION IN WIRELESS NETWORKS BASED ON ARTIFICIAL NOISE - Kudrenko, Stanislava; Kozlovsky, Valeriy; Stoliar, Anna (Ukrainian Information Security Research Journal, 2024)
Adaptive interference suppression based on artificial noise is a promising approach to enhancing the security of wireless networks. In traditional cryptographic protection systems, attackers can exploit physical-layer attacks to intercept signals. One of the effective protection methods is the use of artificial noise (AN), which generates specially designed interference to complicate unauthorized access. This paper investigates the principles of adaptive artificial noise power control using the gradient descent method. The proposed approach enables dynamic noise level regulation based on communication channel parameters such as attacker distance, signal strength, and environmental interference. The modeling was conducted using an open-source wireless sensor network (WSN) dataset, allowing us to evaluate the impact of adaptive noise on packet loss and signal strength. The results demonstrate that the optimized method effectively reduces the probability of interception without significantly degrading the communication quality for legitimate users. The proposed model can be applied in modern mobile communication systems, IoT networks, and critical infrastructures requiring an increased level of data protection.