The Role of Artificial Intelligence in Cybersecurity: A Deep Learning Approach to Securing Digital Infrastructure
DOI:
https://doi.org/10.22399/ijcesen.4359Keywords:
Artificial Intelligence, Cybersecurity, Bidirectional Deep Learning, Threat Detection, Digital Infrastructure, Convolutional Neural NetworksAbstract
The goal of the research is to answer how deep learning techniques affect the accuracy of threat detection, threat response automation and the security of the digital infrastructure in general. These days, security measures can hardly defend against increasingly sophisticated cyber-attacks, including ransomware, phishing and even zero-day vulnerabilities. The rapid digitalization of modern-day industries, the increasing complexities of cyber threats have made the utilization of AI in cybersecurity imperative. As a set of traditional measures is unable to defend against these kinds of attacks, new emerging technologies such as deep learning are set to make an impact. AI and deep learning in particular, is set to make strides in the active, preventive and mitigative measures of cyber-attack threats. These goals achieved by employing a systematic literature review hybridized with deep learning model experimentation concerning the field of cybersecurity. Recent developments in the integration of AI in security measures reviewed, along with numerous neural networks CNNs, RNNs and GANs. It is implementing an experimental design and evaluation with a benchmark dataset pertaining to cybersecurity. The conclusion highlights that deep learning greatly improves threat detection mechanisms through automation in cybersecurity. Compared to conventional security systems, machine learning models offer higher mastery in identifying anomalies and produce fewer false alarms. There are still some obstacles like the complexity of computations, opposing threats and privacy issues. These findings suggest that AI-powered cybersecurity solutions greatly enhance the protection of national critical assets and infrastructures in a rapidly changing cyber environment.
References
Abbas, N. N., Ahmed, T., Shah, S. H. U., Omar, M., & Park, H. W. (2019). Investigating the applications of artificial intelligence in cyber security. Scient metrics, 121, 1189-1211.
Adewusi, A. O., Okoli, U. I., Olorunsogo, T., Adaga, E., Daraojimba, D. O., & Obi, O. C. (2024). Artificial intelligence in cybersecurity: Protecting national infrastructure: A USA. World Journal of Advanced Research and Reviews, 21(1), 2263-2275.
Akhtar, M., & Feng, T. (2021). An overview of the applications of Artificial Intelligence in Cybersecurity. EAI endorsed transactions on creative technologies, 8(29).
Akhtar, Z. B., & Rawol, A. T. (2024). Enhancing cybersecurity through AI-powered security mechanisms. IT Journal Research and Development, 9(1), 50-67.
Al-Hawawreh, M., Moustafa, N., Garg, S., & Hossain, M. S. (2020). Deep learning-enabled threat intelligence scheme in the internet of things networks. IEEE Transactions on Network Science and Engineering, 8(4), 2968-2981.
Alsoufi, M. A., Razak, S., Siraj, M. M., Nafea, I., Ghaleb, F. A., Saeed, F., & Nasser, M. (2021). Anomaly-based intrusion detection systems in iot using deep learning: A systematic literature review. Applied sciences, 11(18), 8383.
Ansari, M. F., Dash, B., Sharma, P., & Yathiraju, N. (2022). The impact and limitations of artificial intelligence in cybersecurity: a literature review. International Journal of Advanced Research in Computer and Communication Engineering.
Apruzzese, G., Colajanni, M., Ferretti, L., Guido, A., & Marchetti, M. (2018, May). On the effectiveness of machine and deep learning for cyber security. In 2018 10th international conference on cyber-Conflict (CyCon) (pp. 371-390). IEEE.
Arif, A., Khan, M. I., & Khan, A. R. A. (2024). An overview of cyber threats generated by AI. International Journal of Multidisciplinary Sciences and Arts, 3(4), 67-76.
Awadallah, A., Eledlebi, K., Zemerly, J., Puthal, D., Damiani, E., Taha, K., ... & Yeun, C. Y. (2024). Artificial intelligence-based cybersecurity for the metaverse: research challenges and opportunities. IEEE Communications Surveys & Tutorials.
binti Burhanuddin, L. A., & Shibghatullah, A. S. B. AI-Enhanced Cybersecurity: A Comprehensive Review of Techniques and Challenges. Current and Future Trends on AI Applications: Volume 1, 107.
Bonfanti, M. E., Cavelty, M. D., & Wenger, A. (2021). Artificial intelligence and cyber-security. In The Routledge Social Science Handbook of AI (pp. 222-236). Routledge.
Camacho, N. G. (2024). The Role of AI in Cybersecurity: Addressing Threats in the Digital Age. Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023, 3(1), 143-154.
Camacho, N. G. (2024). The Role of AI in Cybersecurity: Addressing Threats in the Digital Age. Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023, 3(1), 143-154.
Carlo, A., Mantı, N. P., WAM, B. A. S., Casamassima, F., Boschetti, N., Breda, P., & Rahloff, T. (2023). The importance of cybersecurity frameworks to regulate emergent AI technologies for space applications. Journal of Space Safety Engineering, 10(4), 474-482.
Catal, C., Giray, G., Tekinerdogan, B., Kumar, S., & Shukla, S. (2022). Applications of deep learning for phishing detection: a systematic literature review. Knowledge and Information Systems, 64(6), 1457-1500.
Chehri, A., Fofana, I., & Yang, X. (2021). Security risk modeling in smart grid critical infrastructures in the era of big data and artificial intelligence. Sustainability, 13(6), 3196.
Chukwunweike, J. N., Yussuf, M., Okusi, O., & Oluwatobi, T. (2024). The role of deep learning in ensuring privacy integrity and security: Applications in AI-driven cybersecurity solutions. World Journal of Advanced Research and Reviews, 23(2), 2550.
Darraj, E., Sample, C., & Justice, C. (2019, July). Artificial intelligence cybersecurity framework: Preparing for the here and now with ai. In ECCWS 2019 18th European Conference on Cyber Warfare and Security (Vol. 132). Academic Conferences and publishing limited.
Darraj, E., Sample, C., & Justice, C. (2019, July). Artificial intelligence cybersecurity framework: Preparing for the here and now with ai. In ECCWS 2019 18th European Conference on Cyber Warfare and Security (Vol. 132). Academic Conferences and publishing limited.
Das, R., & Sandhane, R. (2021, July). Artificial intelligence in cyber security. In Journal of Physics: Conference Series (Vol. 1964, No. 4, p. 042072). IOP Publishing.
Das, R., & Sandhane, R. (2021, July). Artificial intelligence in cyber security. In Journal of Physics: Conference Series (Vol. 1964, No. 4, p. 042072). IOP Publishing.
Familoni, B. T. (2024). Cybersecurity challenges in the age of AI: theoretical approaches and practical solutions. Computer Science & IT Research Journal, 5(3), 703-724.
Familoni, B. T. (2024). Cybersecurity challenges in the age of AI: theoretical approaches and practical solutions. Computer Science & IT Research Journal, 5(3), 703-724.
Garcia, A. B., Babiceanu, R. F., & Seker, R. (2021, April). Artificial intelligence and machine learning approaches for aviation cybersecurity: An overview. In 2021 integrated communications navigation and surveillance conference (ICNS) (pp. 1-8). IEEE.
Ghillani, D. (2022). Deep learning and artificial intelligence framework to improve the cyber security. Authorea Preprints.
Islam, S., Hayat, M. A., & Hossain, M. F. (2023). ARTIFICIAL INTELLIGENCE FOR CYBERSECURITY: IMPACT, LIMITATIONS AND FUTURE RESEARCH DIRECTIONS.
Jimmy, F. (2021). Emerging threats: The latest cybersecurity risks and the role of artificial intelligence in enhancing cybersecurity defenses. Valley International Journal Digital Library, 564-574.
Kalnawat, A., Dhabliya, D., Vydehi, K., Dhablia, A., & Kumar, S. D. (2024). Safeguarding Critical Infrastructures: Machine Learning in Cybersecurity. In E3S Web of Conferences (Vol. 491, p. 02025). EDP Sciences.
Khan, M. I., Arif, A., & Khan, A. R. A. (2024). The Most Recent Advances and Uses of AI in Cybersecurity. BULLET: Jurnal Multidiscipline Ilmu, 3(4), 566-578.
Kumar, S., Gupta, U., Singh, A. K., & Singh, A. K. (2023). Artificial intelligence: revolutionizing cyber security in the digital era. Journal of Computers, Mechanical and Management, 2(3), 31-42.
Macas, M., Wu, C., & Fuertes, W. (2022). A survey on deep learning for cybersecurity: Progress, challenges, and opportunities. Computer Networks, 212, 109032.
Magfiroh, D. (2025). Artificial intelligence in cybersecurity risk analysis on national vital infrastructure. Journal of Artificial Intelligence Research, 1(1), 1-10.
Mahdavifar, S., & Ghorbani, A. A. (2019). Application of deep learning to cybersecurity: A survey. Neurocomputing, 347, 149-176.
Mahdavifar, S., & Ghorbani, A. A. (2019). Application of deep learning to cybersecurity: A survey. Neurocomputing, 347, 149-176.
Manoharan, A., & Sarker, M. (2023). Revolutionizing Cybersecurity: Unleashing the Power of Artificial Intelligence and Machine Learning for Next-Generation Threat Detection. DOI: https://www. doi. org/10.56726/IRJMETS32644, 1.
Mijwil, M. M., Salem, I. E., & Ismaeel, M. M. (2023). The significance of machine learning and deep learning techniques in cybersecurity: A comprehensive review. Iraqi Journal For Computer Science and Mathematics, 4(1), 10.
Mijwil, M. M., Salem, I. E., & Ismaeel, M. M. (2023). The significance of machine learning and deep learning techniques in cybersecurity: A comprehensive review. Iraqi Journal For Computer Science and Mathematics, 4(1), 10.
Mijwil, M. M., Salem, I. E., & Ismaeel, M. M. (2023). The significance of machine learning and deep learning techniques in cybersecurity: A comprehensive review. Iraqi Journal For Computer Science and Mathematics, 4(1), 10.
Morel, B. (2011, October). Artificial intelligence and the future of cybersecurity. In Proceedings of the 4th ACM workshop on Security and artificial intelligence (pp. 93-98).
Mughaid, A., AlZu’bi, S., Hnaif, A., Taamneh, S., Alnajjar, A., & Elsoud, E. A. (2022). An intelligent cyber security phishing detection system using deep learning techniques. Cluster Computing, 25(6), 3819-3828.
Paramesha, M., Rane, N. L., & Rane, J. (2024). Artificial intelligence, machine learning, and deep learning for cybersecurity solutions: a review of emerging technologies and applications. Partners Universal Multidisciplinary Research Journal, 1(2), 84-109.
Roshanaei, M., Khan, M. R., & Sylvester, N. N. (2024). Enhancing cybersecurity through AI and ML: Strategies, challenges, and future directions. Journal of Information Security, 15(3), 320-339.
Sahingoz, O. K., BUBE, E., & Kugu, E. (2024). Dephides: Deep learning-based phishing detection system. IEEE Access, 12, 8052-8070.
Salih, A., Zeebaree, S. T., Ameen, S., Alkhyyat, A., & Shukur, H. M. (2021, February). A survey on the role of artificial intelligence, machine learning and deep learning for cybersecurity attack detection. In 2021 7th International Engineering Conference “Research & Innovation amid Global Pandemic"(IEC) (pp. 61-66). IEEE.
Salloum, S. A., Alshurideh, M., Elnagar, A., & Shaalan, K. (2020, March). Machine learning and deep learning techniques for cybersecurity: a review. In The International Conference on Artificial Intelligence and Computer Vision (pp. 50-57). Cham: Springer International Publishing.
Sarker, I. H. (2021). Deep cybersecurity: a comprehensive overview from neural network and deep learning perspective. SN Computer Science, 2(3), 154.
Sarker, I. H. (2023). Machine learning for intelligent data analysis and automation in cybersecurity: current and future prospects. Annals of Data Science, 10(6), 1473-1498.
Sarker, I. H. (2023). Multi‐aspects AI‐based modeling and adversarial learning for cybersecurity intelligence and robustness: A comprehensive overview. Security and Privacy, 6(5), e295.
Schmitt, M. (2023). Securing the Digital World: Protecting smart infrastructures and digital industries with Artificial Intelligence (AI)-enabled malware and intrusion detection. Journal of Industrial Information Integration, 36, 100520.
Shah, V. (2021). Machine Learning Algorithms for Cybersecurity: Detecting and Preventing Threats. Revista Espanola de Documentation Cientifica, 15(4), 42-66.
Suresh, P., Logeswaran, K., Keerthika, P., Devi, R. M., Sentamilselvan, K., Kamalam, G. K., & Muthukrishnan, H. (2022). Contemporary survey on effectiveness of machine and deep learning techniques for cyber security. In Machine Learning for Biometrics (pp. 177-200). Academic Press.
Waizel, G. (2024, July). Bridging the AI divide: The evolving arms race between AI-driven cyber-attacks and AI-powered cybersecurity defenses. In International Conference on Machine Intelligence & Security for Smart Cities (TRUST) Proceedings (Vol. 1, pp. 141-156).
Yang, W., & Lam, K. Y. (2020). Automated cyber threat intelligence reports classification for early warning of cyber-attacks in next generation SOC. In Information and Communications Security: 21st International Conference, ICICS 2019, Beijing, China, December 15–17, 2019, Revised Selected Papers 21 (pp. 145-164). Springer International Publishing.
Zhang, Z., Ning, H., Shi, F., Farha, F., Xu, Y., Xu, J., ... & Choo, K. K. R. (2022). Artificial intelligence in cyber security: research advances, challenges, and opportunities. Artificial Intelligence Review, 1-25.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 International Journal of Computational and Experimental Science and Engineering
This work is licensed under a Creative Commons Attribution 4.0 International License.
