The efficacy of Deep Learning and Artificial Intelligence framework in enhancing Cybersecurity, Challenges and Future Prospects

Abstract

This paper stresses the need of recognizing network threats and intrusion detection systems in the ever-changing cybersecurity environment. The paper discusses how increased data transfer rates affect Intrusion Detection Systems (IDS) and how deep learning is vital to cybersecurity.  The paper categorizes cyberattacks by their goals and techniques, emphasizing the need for modern defenses. This paper examines the intricate relationships between machine learning, deep learning, and artificial intelligence, describing their roles and strengths and drawbacks.  The research shows that machine learning and deep learning can analyze vast datasets, find complicated patterns, and work in real time, making them crucial to cyber risk mitigation. AI technology like ChatGPT may be used in cybersecurity. Exploring cybersecurity challenges, developments, and trends, highlighting the need for modern technologies and the ever-changing cyber threat scenario. As they integrate with new technologies, machine learning and deep learning will improve cybersecurity threat detection and digital identity protection.