Abstract: In the area of machine learning (ML ... The innovative method of compact data design for optimizing ML training through dataset reduction is proposed. The performance of an ML-based malware ...

In his paper “Malware Detection Using Machine Learning” Dragos Gavrilut aimed for developing a detection system based on several modified perceptron algorithms. For different algorithms, he achieved ...

Abstract: Applications of Machine Learning (ML) algorithms in cybersecurity provide significant performance enhancement over traditional rule-based ... detection system to formulate security analysts' ...

Whether you’re an individual or a company, safeguarding your data is of utmost importance. One effective approach to protect sensitive information and systems is by utilising tools powered by ...

--(BUSINESS WIRE)--FireEye, Inc. (NASDAQ: FEYE), the intelligence-led security company, today announced the addition of MalwareGuard™ – a new advanced machine learning based detection and ...

Advanced malware can change forms to evade detection, and using a traditional signature-based approach makes ... a life or death impact. If a machine learning system mistakes a fraudulent data ...

Padamati's prowess in automated machine learning ... threat detection and response systems to combat sophisticated cyber attacks. The rise of AI-generated phishing emails, automated malware ...

Advanced machine learning ... fraud detection systems must evolve to match and surpass their capabilities. Speed, scalability, and adaptability will be critical design principles for the next ...