Detection Malware Attacks by Using Data Analytics and Deep Learning

The increasing frequency and complexity of cyberattacks have made it vital to utilize various strategies to prevent attackers from accessing sensitive data. One effective method is using machine learning to analyze network traffic for potential threats. Researchers heavily rely on machine learning and deep learning techniques like Recurrent Neural Network (RNN), Long-Short Term Memory Recurrent Neural Network (LSTM-RNN), and Convolutional Neural Network (CNN) for creating resilient models with accurate prediction capabilities to detect cyber threats. This study aims to evaluate these deep learning algorithms' effectiveness in identifying cyberattacks and explore ways to enhance cybersecurity through effective strategies.

Keywords:

Machine Learning , Deep Learning , Neural Networks , Recurrent Neural Network , Convolutional Neural Network