Why Australia Is a Prime Target for AI Identity Attacks

Australia's enterprise sector faces rising risks from AI-driven identity attacks. Learn what Australian challenged ...
IEEE

AI Powered Network Intrusion Detection System Using Machine Learning

Abstract: This study presents a machine-learning-based Network Intrusion Detection System (NIDS) designed to overcome the limitations of traditional signature-based IDS, such as low accuracy and poor ...
IEEE

ZTID-IoV: Zero-Trust Intrusion Detection in IoV Using Neurosymbolic AI Approach With Federated Meta-Learning

Abstract: The rapid growth of the Internet of Vehicles (IoVs) and smart consumer electronics has generated cybersecurity concerns that require an intelligent, adaptable, and privacy-preserving ...
Journal of Medical Internet Research

Prediction of Moderate-to-Severe Sepsis-Associated Acute Kidney Injury Using a Dual-Timepoint Machine Learning Model: Development, Multiregional Validation, and Clinical ...

Based on clinical data from the first 24 hours of ICU admission, we used a two-stage feature selection process combining light gradient boosting machine (LightGBM) and Shapley additive explanation ...