Malware Detection Using Deep Learning and Correlation-Based Feature Selection

• المؤلفون الرئيسيون: Alomari E.S., Nuiaa R.R., Alyasseri Z.A.A., Mohammed H.J., Sani N.S., Esa M.I., Musawi B.A.
• مؤلفون آخرون: 58668473000
• التنسيق: مقال
• منشور في: MDPI 2024
• الموضوعات: deep learning; dense model; feature selection; LSTM; malware detection

Malware is one of the most frequent cyberattacks, with its prevalence growing daily across the network. Malware traffic is always asymmetrical compared to benign traffic, which is always symmetrical. Fortunately, there are many artificial intelligence techniques that can be used to detect malware an...