Authors : Diwakar Mainali; Megan Nagarkoti; Saraswoti Shrestha; Umesh Thapa; Dr. Om Prakash Sharma

Volume/Issue : Volume 9 - 2024, Issue 8 - August

Google Scholar : https://tinyurl.com/3e3t834w

Scribd : https://rb.gy/bg9q7n

DOI : https://doi.org/10.38124/ijisrt/IJISRT24AUG482

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Cybersecurity experts are increasingly combining AI and ML because cyber threats are growing so quickly and better ways to find and stop them are needed. Using AI and ML to find threats better is what this study article is mostly about. To begin, it gives a broad outline of the current state of cyber threats and the problems with current methods of finding. The study looks at different AI and ML methods, such as supervised, unstructured, and deep learning, as possible ways to find and stop hacking threats. A lot of relevant study and papers are looked at to show that these tools work. Firstly, we will look at the differences and similarities between the different AI and ML methods. Afterward, we will talk about the pros and cons of these tools. In the end, the paper shows the findings and stresses how important these technologies are for providing a strong defence against sophisticated cyberattacks. The possible results and progress of AI and ML in the area of cybersecurity are also talked about.

Keywords : Artificial Intelligence (AI), Machine Learning (ML), Cybersecurity, Threat Detection, Supervised Learning, Unsupervised Learning.

References :

1. U. I. Okoli, O. C. Obi, A. O. Adewusi, and T. O. Abrahams, "Machine learning in cybersecurity: A review of threat detection and defense mechanisms," World Journal of Advanced Research and Reviews, vol. 21, no. 1, pp. 2286-2295, 2024.
2. Manoharan and M. Sarker, "Revolutionizing Cybersecurity: Unleashing the Power of Artificial Intelligence and Machine Learning for Next-Generation Threat Detection," DOI: https://www.doi.org/10.56726/IRJMETS32644,2023
3. Ibrahim, "The Cyber Frontier: AI and ML in Next-Gen Threat Detection," 2019.
4. Manoharan and M. Sarker, "Revolutionizing Cybersecurity: Unleashing the Power of Artificial Intelligence and Machine Learning for Next-Generation Threat Detection," DOI: https://www.doi.org/10.56726/IRJMETS3 2644, 2023.
5. Shukla, "Leveraging AI and ML for Advance Cyber Security," Journal of Artificial Intelligence & Cloud Computing, vol. SRC/JAICC-154, DOI: doi.org/10.47363/JAICC/2022, pp. 2-3, 2022.
6. R. Maddireddy and B. R. Maddireddy, "Proactive Cyber Defense: Utilizing AI for Early Threat Detection and Risk Assessment," International Journal of Advanced Engineering Technologies and Innovations, vol. 1, no. 2, pp. 64-83, 2020.
7. M. Sewak, S. K. Sahay, and H. Rathore, "Deep reinforcement learning in the advanced cybersecurity threat detection and protection," Information Systems Frontiers, vol. 25, no. 2, pp. 589-611, 2023.
8. J. H. Li, "Cyber security meets artificial intelligence: a survey," Frontiers of Information Technology & Electronic Engineering, vol. 19, no. 12, pp. 14621474, 2018.

9. M. Rizvi, "Enhancing cybersecurity: The power of artificial intelligence in threat detection and prevention," International Journal of Advanced Engineering Research and Science, vol. 10, no. 05, 2023.
10. R. Maddireddy and B. R. Maddireddy, "Evolutionary Algorithms in AI-Driven Cybersecurity Solutions for Adaptive Threat Mitigation," International Journal of Advanced Engineering Technologies and Innovations, vol. 1, no. 2, pp. 17-43, 2021.
11. M. Sewak, S. K. Sahay, and H. Rathore, "Deep reinforcement learning for cybersecurity threat detection and protection: A review," in International Conference On Secure Knowledge Management In Artificial Intelligence Era, Cham: Springer International Publishing, 2021, pp. 51-72.
12. Dasgupta, Z. Akhtar, and S. Sen, "Machine learning in cybersecurity: a comprehensive survey," The Journal of DefenseModeling and Simulation, vol. 19, no. 1, pp. 57-106, 2022.
13. M. Omar, "Application of machine learning (ML) to address cybersecurity threats," in Machine Learning for Cybersecurity: Innovative Deep Learning Solutions, Cham: Springer International Publishing, 2022, pp. 1-11.
14. Yaseen, "AI-driven threat detection and response: A paradigm shift in cybersecurity," International Journal of Information and Cybersecurity, vol. 7, no. 12, pp. 25-43, 2023.
15. G. Apruzzese, P. Laskov, E. Montes de Oca, W. Mallouli, L. Brdalo Rapa, A. V. Grammatopoulos, and F. Di Franco, "The role of machine learning in cybersecurity," Digital Threats: Research and Practice, vol. 4, no. 1, pp. 1-38, 2023.
16. K. Hasan, S. Shetty, and S. Ullah, "Artificial intelligence empowered cyber threat detection and protection for power utilities," in 2019 IEEE 5th international conference on collaboration and internet computing (CIC), IEEE, 2019, pp. 354359.
17. V. Shah, "Machine Learning Algorithms for Cybersecurity: Detecting and Preventing Threats," Revista Espanola de DocumentacionCientifica, vol. 15, no. 4, pp. 42-66, 2021.
18. O. M. Ijiga, I. P. Idoko, G. I. Ebiega, F. I. Olajide, T. I. Olatunde, and C. Ukaegbu, "Harnessing adversarial machine learning for advanced threat detection: AIdriven strategies in cybersecurity risk assessment and fraud prevention," 2024.
19. M. Abdullahi, Y. Baashar, H. Alhussian, A. Alwadain, N. Aziz, L. F. Capretz, and S. J. Abdulkadir, "Detecting cybersecurity attacks in internet of things using artificial intelligence methods: A systematic literature review," Electronics, vol. 11, no. 2, p. 198, 2022.
20. S. Duary, P. Choudhury, S. Mishra, V. Sharma, D. D. Rao, and A. P. Aderemi, "Cybersecurity Threats Detection in Intelligent Networks using Predictive Analytics Approaches," in 2024 4th International Conference on Innovative Practices in Technology and Management (ICIPTM), IEEE, 2024, pp. 1-5.
21. S. A. Vaddadi, R. Vallabhaneni, and P. Whig, "Utilizing AI and Machine Learning in Cybersecurity for Sustainable Development through Enhanced Threat Detection and Mitigation," International Journal of Sustainable Development Through AI, ML and IoT, vol. 2, no. 2, pp. 1-8, 2023.
22. Salih, S. T. Zeebaree, S. Ameen, A. Alkhyyat, and H. M. Shukur, "A survey on the role of artificial intelligence, machine learning and deep learning for cybersecurity attack detection," in 2021 7th International Engineering Conference
23. “Research & Innovation amid Global Pandemic" (IEC), IEEE, 2021, pp. 61-66.
24. R. Calderon, "The benefits of artificial intelligence in cybersecurity," 2019.
25. N. Mohamed, "Current trends in AI and ML for cybersecurity: A state-of-theart survey," Cogent Engineering, vol. 10, no. 2, p. 2272358, 2023.
26. N. G. Camacho, "The Role of AI in Cybersecurity: Addressing Threats in the Digital Age," Journal of Artificial Intelligence General Science (JAIGS), vol. 3, no. 1, pp. 143-154, 2024.
27. B. R. Maddireddy and B. R. Maddireddy, "Adaptive Cyber Defense: Using Machine Learning to Counter Advanced Persistent Threats," International Journal of Advanced Engineering Technologies and Innovations, vol. 1, no. 3, pp. 305-324, 2023.
28. K. R. Dalal and M. Rele, "Cyber Security: Threat Detection Model based on Machine learning Algorithm," in 2018 3rd International Conference on Communication and Electronics Systems (ICCES), IEEE, 2018, pp. 239-243.
29. R. Badhwar, "The Case for AI/ML in Cybersecurity," in The CISO’s Next Frontier: AI, Post-Quantum Cryptography and Advanced Security Paradigms, Cham: Springer International Publishing, 2021, pp. 45-73.
30. H. Chaudhary, A. Detroja, P. Prajapati, and P. Shah, "A review of various challenges in cybersecurity using artificial intelligence," in 2020 3rd international conference on intelligent sustainable systems (ICISS), IEEE, 2020, pp. 829-836.
31. Ibrahim, "Guardians of the Virtual Gates: Unleashing AI for Next-Gen Threat Detection in Cybersecurity," 2022.
32. L. Pissanidis and K. Demertzis, "Integrating AI/ML in Cybersecurity: An Analysis of Open XDR Technology and its Application in Intrusion Detection and System Log Management," 2023.
33. L. Kasowaki and K. Emir, "AI and Machine Learning in Cybersecurity: Leveraging Technology to Combat Threats," EasyChair, no. 11610, 2023.
34. B. Geluvaraj, P. M. Satwik, and T. A. Ashok Kumar, "The future of cybersecurity: Major role of artificial intelligence, machine learning, and deep learning in cyberspace," in International Conference on Computer Networks and Communication Technologies: ICCNCT 2018, Springer Singapore, 2019, pp. 739747.