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 ...
Microsoft

GigaWiper: Anatomy of a destructive backdoor assembled from multiple malware

GigaWiper is a destructive backdoor that combines multiple wiping and ransomware-like capabilities into a single operational ...
Tech Xplore

New federated learning algorithm enables private, robust, and fast AI development

Three heads are better than one. Versions of this proverb are found worldwide and throughout history. Yet in the race to ...

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 ...
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 ...
IEEE

Intrusion Prevention System Optimization Using Machine Learning

Abstract: The growing reliance on networked systems continues to increase the risk of cyberattacks, particularly denial-of-service (DoS) and distributed denial-of-service (DDoS) threats targeting ...