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How to build a robust Windows service to block malware and ransomware
Designing a security-focused Windows Service? Learn more from ThreatLocker about the core components for real-time monitoring ...
Scientific Research Publishing3d
A Comparative Study of Ensemble Learning Techniques and Classification Models to Identify Phishing Websites ()
Budoen, A.T., Zhang, M.W. and Edwards Jr., L.Z. (2025) A Comparative Study of Ensemble Learning Techniques and Classification Models to Identify Phishing Websites. Open Access Library Journal, 12, ...
Que.com on MSN4d
Cybersecurity Weekly Recap: AI Malware and Zero-Click Exploit Threats
In an era of digitization, where data serves as the new gold, the cybersecurity landscape continues to evolve rapidly. Each ...
IEEE4d
Zero-Day Malware Detection through Unsupervised Deep Learning
Abstract: This paper investigates the problem of zero-day malicious software (Malware) detection through unsupervised deep learning. We built a sequence-to-sequence auto-encoder model for learning the ...
IEEE5d
Network Attack Detection using Machine Learning
Intrusion detection systems are used for this purpose. We have used a few of the Machine Learning (ML) procedures such as Support vector Machine (SVM), Decision Tree (DT), Logistic regression (LR), ...