• Chandana V S
• Shalini S

The rapid growth in the usage of Computer Networks has significantly expanded the attack of modern networks, making them increasingly more vulnerable to threats in cyber network. Traditional threat detection techniques often has limitations to keep up with the dynamic nature and abundant volume of data. Deep learning (DL), a subfield of machine learning, has emerged as a promising approach for automating and enhancing cybersecurity in Computer Networks. This paper explores the existing methods to detect and mitigate the cyber threats in Computer Networks, by prioritizing their ability to identify sophisticated attack patterns by highking them, adapt to dynamic network conditions, and in turn improve the accuracy of cyber network over time. The paper also discusses the future aspects of research carried out in the cyber security sector and threat mitigation using Artificial intelligence (AI), along with Machine Learning (ML) and Natural Language Processing(NLP).

Cyber-attack, Cyber security, Mitigation, Deep Learning.

"A REVIEW ON APPROACHES FOR CYBER THREAT DETECTION AND MITIGATION TECHNIQUES USING ARTIFICIAL INTELLIGENCE AND INTERNET OF THINGS ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 2, page no.g638-g642, February-2025, Available :http://www.jetir.org/papers/JETIR2502675.pdf

"A REVIEW ON APPROACHES FOR CYBER THREAT DETECTION AND MITIGATION TECHNIQUES USING ARTIFICIAL INTELLIGENCE AND INTERNET OF THINGS ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 2, page no. ppg638-g642, February-2025, Available at : http://www.jetir.org/papers/JETIR2502675.pdf