A study by researchers from BRAC University produced a malware detection system with a 99.99% accuracy rate in binary classification tests. The system was developed using multiple machine learning strategies, including an Adaptive Synthetic Sampling (ADASYN) approach for imbalanced data, which proved most effective. The research emphasizes the importance of a comprehensive defense strategy including machine learning to combat the ever-evolving threat of malware. Future research should focus on refining these algorithms.

‘Systemic gaps’ found private equity-backed healthcare companies’ cybersecurity preparedness
Private equity-backed healthcare companies have “systemic gaps” in their cybersecurity preparedness, according to a report from Clearwater Security. The findings revealed many such firms lack