IEEE

A Comprehensive Survey on Cognitive Cyber Security Analysis Using Machine Learning Approaches

Abstract: Cybersecurity threats have evolved in sophistication, necessitating the development of intelligent and adaptive defense mechanisms. Cognitive cybersecurity systems present the opportunity to ...
Opinion
Tech XploreOpinion

Generative AI may cut costs in machine-learning systems, but it increases risks of cyberattacks and data leaks

Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper appearing in Patterns. Though large language models ...
SDxCentral

Cato Networks launches security and AI-driven analysis features

Secure access service edge (SASE) vendor Cato Networks has announced two additions to its Cato SASE Platform to secure enterprise AI adoption at scale. The firm introduced Cato Neural Edge, deploying ...
techtimes

AI Cyberattacks Rising: How Hackers Use Machine Learning to Launch Smarter Attacks

AI cyberattacks are rapidly transforming the cybersecurity landscape, enabling attackers to automate and scale operations with unprecedented speed. Through machine learning hacking, adversaries can ...
The Lancet

When to and when not to use machine learning in risk prediction models

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...
FedScoop

ICE drives AI use case growth within Homeland Security

ICE agents leave a residence after knocking on the door on Jan. 28, 2026 in Minneapolis, Minnesota. The U.S. Department of Homeland Security continues its immigration enforcement operations after two ...
Frontiers

Hybrid optimization of interpretable ensemble machine learning for petrophysical property prediction from well logs

Unconventional reservoirs, including shale gas, tight oil, and coalbed methane formations, have emerged as vital contributors to global energy security, accounting for a substantial portion of the ...
IEEE

VISION LOG: CCTV Footage Timestamp Analysis Using Machine Learning Algorithms

Abstract: With the increase in adoption of CCTV surveillance systems in both private and public spaces, the need for developing intelligent systems for automatic video analysis has augmented. This ...
acm.org

Integrating Machine Learning into Physical Security Architecture

Recent advancements in the field of artificial intelligence (AI) have exposed many modern organizations to the benefits of intelligent automation. According to research published by McKinsey, almost ...
Morningstar

Machine Learning Can Forecast Which Stock Factors Will Outperform

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...
National Academies of Sciences%2c Engineering%2c and Medicine

Making Machine Learning Safer in High-Stakes Settings

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...
Rochester Institute of Technology

RIT researchers use machine learning to better understand the pathways of disease

Cancer, Alzheimer’s, and other diseases follow a pathway in the human body. It starts at the molecular and cellular levels, and through a series of complex interactions can lead to the development and ...