Rey et al. (2022) proposed a security framework that utilizes the FL procedure to detect and identify malware affecting IoT infrastructure in a privacy-preserving manner. This framework integrates ...

Threat intelligence firm Recorded Future Inc. today announced the launch of Malware Intelligence, a new platform designed to automate the detection of emerging malware threats, speed up threat ...

A University of Cincinnati study found machine learning models can aid in the automation and detection of abnormal ... SD events that were not identified using human scoring, likely due to a ...

This review discusses the current state of multicancer early detection tests, the role of machine learning in their development, and their implications for oncology practice and patient care. THE ...

They concluded that a deep learning approach could lead to a smart anti-malware program. Yanfang et al. (2017) provided a complete survey on malware detection techniques using machine learning. They ...

Rabadi’s research paper, titled “BERT-Cuckoo15: A Comprehensive Framework for Malware Detection Using 15 Dynamic Feature Types ... outperforming traditional machine learning models. According to ...

This project utilizes machine learning techniques to build a robust malware detection system capable of analyzing files ... to ensure consistency and includes features extracted using static and ...

Organisations are increasingly using ... Advanced malware detection employs a range of techniques to detect and analyse malware, including behavioural analysis, machine learning, signature-based ...