Yichuang Sun, Haeyoung Lee, Oluyomi Simpson
The landscape of communication environments is undergoing a revolutionary transformation, driven by the relentless evolution of technology and the growing demands of an interconnected world [...]
Chittathuru Himala Praharsha, Alwin Poulose, Chetan Badgujar
Deep learning applications in agriculture are advancing rapidly, leveraging data-driven learning models to enhance crop yield and nutrition. Tomato (Solanum lycopersicum), a vegetable crop, frequently suffers from pest damage and drought, leading to reduced yields and financial l…
Mohammed Alkhowaiter, Hisham Kholidy, Mnassar A. Alyami, Abdulmajeed Alghamdi, Cliff Zou
Deep learning models have been used in creating various effective image classification applications. However, they are vulnerable to adversarial attacks that seek to misguide the models into predicting incorrect classes. Our study of major adversarial attack models shows that the…
Haeyoung Lee, Yichuang Sun, Oluyomi Simpson
Machine learning (ML) has been increasingly considered for various communication applications, demonstrating promising feasibility and effectiveness in enhancing system intelligence, adaptability, and operational efficiency [...]
Annisa Anggun Puspitasari, To Truong An, Mohammed H. Alsharif, Byung Moo Lee
The fifth generation achieved tremendous success, which brings high hopes for the next generation, as evidenced by the sixth generation (6G) key performance indicators, which include ultra-reliable low latency communication (URLLC), extremely high data rate, high energy and spect…
Joaquín Gaspar Medina-Arco, Roberto Magán-Carrión, Rafael Alejandro Rodríguez-Gómez, Pedro García-Teodoro
With the significant increase in cyber-attacks and attempts to gain unauthorised access to systems and information, Network Intrusion-Detection Systems (NIDSs) have become essential detection tools. Anomaly-based systems use machine learning techniques to distinguish between norm…
Subhita Menon, Divya Anand, Kavita, Sahil Verma, Manider Kaur, N. Z. Jhanjhi, et al.
With the increasing growth rate of smart home devices and their interconnectivity via the Internet of Things (IoT), security threats to the communication network have become a concern. This paper proposes a learning engine for a smart home communication network that utilizes bloc…