A Survey on the Role of Artificial Intelligence, Machine Learning and Deep Learning for Cybersecu...

1. INTRODUCTION

1.1. Cybersecurity is defined as the protection of computer systems and networks from unauthorized access

1.2. Growth in IoT, smart devices, cloud computing, and wireless networking has created major security challenges

1.3. IDS (Intrusion Detection Systems) helps discover, monitor, and analyze different types of attacks on network traffic

2. ARTIFICIAL INTELLIGENCE IN CYBER SECURITY

2.1. MACHINE LEARNING IN CYBER SECURITY

2.2. DEEP LEARNING IN CYBER SECURITY

3. LITERATURE REVIEW

3.1. Reviews numerous implementations of AI, ML, and DL in cybersecurity from 2018-2020

4. DISCUSSION AND COMPARISON

4.1. Deep learning performs better than traditional approaches for malicious threat detection

4.2. Hybrid algorithms and multi-algorithm combinations provide optimal solutions

4.3. Challenges in deep learning implementation: 1- Requires immense processing power 2- Needs large amounts of data

5. CONCLUSION

5.1. Cybersecurity aims to protect systems from unauthorized access and damage

5.2. Developing intelligent cybersecurity models is essential for analyzing large datasets

5.3. AI, machine learning, and deep learning are increasingly used for threat detection and Deep learning is the most effective approach for handling complex data