Waleed Aldosari^*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1253-1269, 2023, DOI:10.32604/cmc.2023.036111

Abstract This paper presents a machine-learning method for detecting jamming UAVs and classifying nodes during jamming attacks on Wireless Sensor Networks (WSNs). Jamming is a type of Denial of Service (DoS) attack and intentional interference where a malicious node transmits a high-power signal to increase noise on the receiver side to disrupt the communication channel and reduce performance significantly. To defend and prevent such attacks, the first step is to detect them. The current detection approaches use centralized techniques to detect jamming, where each node collects information and forwards it to the base station. As a result, overhead and communication costs… More >

Mohammed S. M. Gismalla^1,2,3, Asrul I. Azmi^1,2, Mohd R. Salim^1,2, Farabi Iqbal^1,2, Mohammad F. L. Abdullah⁴, Mosab Hamdan^5,6, Muzaffar Hamzah^5,*, Abu Sahmah M. Supa’at^1,2

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3607-3625, 2023, DOI:10.32604/cmc.2023.031192

Abstract Visible light communication (VLC), which is a prominent emerging solution that complements the radio frequency (RF) technology, exhibits the potential to meet the demands of fifth-generation (5G) and beyond technologies. The random movement of mobile terminals in the indoor environment is a challenge in the VLC system. The model of optical attocells has a critical role in the uniform distribution and the quality of communication links in terms of received power and signal-to-noise ratio (SNR). As such, the optical attocells positions were optimized in this study with a developed try and error (TE) algorithm. The optimized optical attocells were examined… More >