5 papers
Online AutoML: Evaluating Poisoning Attacks on Cost-Utility Adversarial Training Defence Strategy for IoT Networks
Chukwunonso Henry Nwokoye, Khalil El-Khatib, Li Yang
Machine learning (ML)-powered poisoning attack vectors are adversarial maneuvers whereby an attacker intentionally inserts, corrupts, or alters training data to distort an ML model…
Evasion Attacks on Cost-Utility-Based Adversarial Training for Online AutoML in IoT Networks
Chukwunonso Henry Nwokoye, Wajiha Zaheer, Khalil El-Khatib +1
As Internet of Things (IoT) networks increasingly depend on machine learning for anomaly, malware, intrusion detection, and network monitoring, such systems have become attractive…
Multi-perspective Imbalance-Conscious 6G Beamforming Optimization and Performance
Chukwunonso Henry Nwokoye, Blessing Oluchi Iloka, Chikwue V. Umeugoji +2
The study presents a systematic machine learning (ML) study of 6G-IoT beamforming optimization (6GBO) using supervised and unsupervised approaches. We compared the predictive power…
Machine Learning Epidemic Predictions Using Agent-based Wireless Sensor Network Models
Chukwunonso Henry Nwokoye, Blessing Oluchi, Sharna Waldron +1
The lack of epidemiological data in wireless sensor networks (WSNs) is a fundamental difficulty in constructing robust models to forecast and mitigate threats such as viruses and w…
A Survey of Accessible Explainable Artificial Intelligence Research
Chukwunonso Henry Nwokoye, Maria J. P. Peixoto, Akriti Pandey +3
The increasing integration of Artificial Intelligence (AI) into everyday life makes it essential to explain AI-based decision-making in a way that is understandable to all users, i…