Deep Learning Models for Cybersecurity in Indian Enterprises: A Comparative Study

Abstract

Indian enterprises are becoming prime targets for cyberattacks, highlighting the need for robust cybersecurity systems. This paper provides a comparative analysis of deep learning models, including Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM), for detecting cyber threats in Indian businesses. The research focuses on identifying advanced threats such as ransomware, phishing, and insider threats by leveraging large-scale enterprise data. By comparing the performance of CNN and LSTM models, the paper highlights their respective strengths in real-time threat detection and sequence data processing. The paper also discusses the practical challenges of implementing deep learning systems in Indian organizations.