Artificial Intelligence

Revolutionizing Cyber Security in the Digital Era


  • Sarvesh Kumar Department of Computer Science Engineering, Babu Banarasi Das University, Lucknow, Uttar pradesh, India 226028
  • Upasana Gupta Department of Computer Science Engineering, Babu Banarasi Das University, Lucknow, Uttar pradesh, India 226028
  • Arvind Kumar Singh Department of Computer Science Engineering, Babu Banarasi Das University, Lucknow, Uttar pradesh, India 226028
  • Avadh Kishore Singh Department of Computer Science Engineering, Babu Banarasi Das University, Lucknow, Uttar pradesh, India 226028



Artificial Intelligence, Cyber Security, Control Distribution, Human Senses Mimicry, Vulnerability Management


As we navigate the digital era of the 21st century, cyber security has grown into a pressing societal issue that requires innovative, cutting-edge solutions. In response to this pressing need, Artificial Intelligence (AI) has emerged as a revolutionary instrument, causing a paradigm shift in cyber security. AI's prowess resides in its capacity to process and analyze immense quantities of heterogeneous cyber security data, thereby facilitating the efficient completion of crucial tasks. These duties, which include threat detection, asset prioritization, and vulnerability management, are performed with a level of speed and accuracy that far exceeds human capabilities, thereby transforming our approach to cyber security. This document provides a comprehensive dissection of AI's profound impact on cyber security, as well as an in-depth analysis of how AI tools not only augment, but in many cases transcend human-mediated processes. By delving into the complexities of AI implementation within the realm of cyber security, we demonstrate the potential for AI to effectively anticipate, identify, and preempt cyber threats, empowering organizations to take a proactive stance towards digital safety. Despite these advancements, it is essential to consider the inherent limitations of AI. We emphasize the need for sustained human oversight and intervention to ensure that cyber security measures are proportionate and effective. Importantly, we address potential ethical concerns and emphasize the significance of robust governance structures for the responsible and transparent use of artificial intelligence in cyber security. This paper clarifies the transformative role of AI in reshaping cyber security strategies, thereby contributing to a safer, more secure digital future. In doing so, it sets the groundwork for further exploration and discussion on the use of AI in cyber security, a discussion that is becoming increasingly important as we continue to move deeper into the digital age.


A. Kish, “Machine Learning: A Review of Methods and Applications,” Researchgate.Net, 2018.

P. Liu and C. Lu, “Strategic analysis and development plan design on digital transformation in the energy industry: A global perspective,” International Journal of Energy Research, vol. 45, pp. 19657–19670, Nov 2021.

J. B. Schmitt, A. Goldmann, S. T. Simon, and C. Bieber, “Conception and Interpretation of Interdisciplinarity in Research Practice: Findings from Group Discussions in the Emerging Field of Digital Transformation,” Minerva, vol. 61, pp. 199–220, Jun 2023.

A. Modi, B. Kishore, D. K. Shetty, V. P. Sharma, S. Ibrahim, R. Hunain, N. Usman, S. G. Nayak, S. Kumar, and R. Paul, “Role of Artificial Intelligence in Detecting Colonic Polyps during Intestinal Endoscopy,” Engineered Science, vol. 20, pp. 23–30, 2022.

D. A. B. Fernandes, L. F. B. Soares, J. V. Gomes, M. M. Freire, and P. R. M. In´acio, “Security issues in cloud environments: a survey,” International Journal of Information Security, vol. 13, pp. 113–170, Apr 2014.

V. Mullet, P. Sondi, and E. Ramat, “A Review of Cybersecurity Guidelines for Manufacturing Factories in Industry 4.0,” IEEE Access, vol. 9, pp. 23235–23263, 2021.

B. Shin and P. B. Lowry, “A review and theoretical explanation of the ‘Cyberthreat-Intelligence (CTI) capability’ that needs to be fostered in information security practitioners and how this can be accomplished,” Computers & Security, vol. 92, p. 101761, May 2020.

M. Naveed Uddin, “Cognitive science and artificial intelligence: simulating the human mind and its complexity,” Cognitive Computation and Systems, vol. 1, pp. 113–116, Dec 2019.

P. Mikalef and M. Gupta, “Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance,” Information & Management, vol. 58, p. 103434, Apr 2021.

A. Kumar, M. Rahmath, Y. Raju, S. Reddy Vulapula, B. R. Prathap, M. M. Hassan, M. A. Mohamed, and S. A. Asakipaam, “Enhanced Secure Technique for Detecting Cyber Attacks Using Artificial Intelligence and Optimal IoT,” Security and Communication Networks, vol. 2022, pp. 1–13, Jul 2022.

R. Trifonov, O. Nakov, and V. Mladenov, “Artificial Intelligence in Cyber Threats Intelligence,” in 2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC), pp. 1–4, IEEE, Dec 2018.

A. Amarasinghe, W. Wijesinghe, D. Nirmana, A. Jayakody, and A. Priyankara, “AI Based Cyber Threats and Vulnerability Detection, Prevention and Prediction System,” in 2019 International Conference on Advancements in Computing (ICAC), pp. 363–368, IEEE, Dec 2019.

R. Gruetzemacher and J. Whittlestone, “The transformative potential of artificial intelligence,” Futures, vol. 135, p. 102884, Jan 2022.

R. Kaur, D. Gabrijelˇciˇc, and T. Klobuˇcar, “Artificial intelligence for cybersecurity: Literature review and future research directions,” Information Fusion, vol. 97, p. 101804, Sep 2023.

M. M. Yamin, M. Ullah, H. Ullah, and B. Katt, “Weaponized AI for cyber attacks,” Journal of Information Security and Applications, vol. 57, 2021.

S. C. Pallaprolu, J. M. Namayanja, V. P. Janeja, and C. T. S. Adithya, “Label propagation in big data to detect remote access Trojans,” in 2016 IEEE International Conference on Big Data (Big Data), pp. 3539–3547, IEEE, Dec 2016.

A. Syrowatka, M. Kuznetsova, A. Alsubai, A. L. Beckman, P. A. Bain, K. J. T. Craig, J. Hu, G. P. Jackson, K. Rhee, and D. W. Bates, “Leveraging artificial intelligence for pandemic preparedness and response: a scoping review to identify key use cases,” Digital Medicine, vol. 4, p. 96, Jun 2021.

M. Ebrahimi, J. F. Nunamaker, and H. Chen, “Semi-Supervised Cyber Threat Identification in Dark Net Markets: A Transductive and Deep Learning Approach,” Journal of Management Information Systems, vol. 37, pp. 694–722, Jul 2020.

Y. Xu, X. Liu, X. Cao, C. Huang, E. Liu, S. Qian, X. Liu, Y. Wu, F. Dong, C.-W. Qiu, J. Qiu, K. Hua, W. Su, J. Wu, H. Xu, Y. Han, C. Fu, Z. Yin, M. Liu, R. Roepman, S. Dietmann, M. Virta, F. Kengara, Z. Zhang, L. Zhang, T. Zhao, J. Dai, J. Yang, L. Lan, M. Luo, Z. Liu, T. An, B. Zhang, X. He, S. Cong, X. Liu, W. Zhang, J. P. Lewis, J. M. Tiedje, Q. Wang, Z. An, F.Wang, L. Zhang, T. Huang, C. Lu, Z. Cai, F.Wang, and J. Zhang, “Artificial intelligence: A powerful paradigm for scientific research,” The Innovation, vol. 2, p. 100179, Nov 2021.

T. Kabudi, I. Pappas, and D. H. Olsen, “AI-enabled adaptive learning systems: A systematic mapping of the literature,” Computers and Education: Artificial Intelligence, vol. 2, p. 100017, 2021.

N. Haefner, J.Wincent, V. Parida, and O. Gassmann, “Artificial intelligence and innovation management: A review, framework, and research agenda,” Technological Forecasting and Social Change, vol. 162, p. 120392, Jan 2021.

G. Banga, “Using Artificial Intelligence in Cybersecurity,” Www.Balbix.Com, 2020.

Y. Li and Q. Liu, “A comprehensive review study of cyber-attacks and cyber security; Emerging trends and recent developments,” Energy Reports, vol. 7, pp. 8176–8186, Nov 2021.

D. Perwej, S. Qamar Abbas, J. Pratap Dixit, D. N. Akhtar, and A. Kumar Jaiswal, “A Systematic Literature Review on the Cyber Security,” International Journal of Scientific Research and Management, vol. 9, pp. 669–710, Dec 2021.

B. Li, Y. Feng, Z. Xiong, W. Yang, and G. Liu, “Research on AI security enhanced encryption algorithm of autonomous IoT systems,” Information Sciences, vol. 575, pp. 379–398, Oct 2021.

S. R. Potula, R. Selvanambi, M. Karuppiah, and D. Pelusi, “Artificial Intelligence-Based Cyber Security Applications,” pp. 343–373, 2023.

M. Graham, R. Kukla, O. Mandrychenko, D. Hart, and J. Kennedy, “Developing Visualisations to Enhance an Insider Threat Product: A Case Study,” in 2021 IEEE Symposium on Visualization for Cyber Security (VizSec), pp. 47–57, IEEE, Oct 2021.

R. Dolas, “Analytic-driven decision support in cybersecurity : towards effective IP risk management decision-making process.,” tech. rep., UNIVERSITY OF TWENTE, 2023.

D. Schlette, “Cyber Threat Intelligence,” in Encyclopedia of Cryptography, Security and Privacy, pp. 1–3, Berlin, Heidelberg: Springer Berlin Heidelberg, 2021.

M. Ahmed, N. Moustafa, A. Barkat, and P. Haskell-Dowland, Next-Generation Enterprise Security and Governance. Boca Raton: CRC Press, Feb 2022.

M. Kaeo, “Designing Network Security,” p. 745, 2003.

J. Cheng, Y. Yang, X. Tang, N. Xiong, Y. Zhang, and F. Lei, “Generative adversarial networks: A literature review,” KSII Transactions on Internet and Information Systems, vol. 14, no. 12, pp. 4625–4647, 2020.

Y. Hu, W. Kuang, Z. Qin, K. Li, J. Zhang, Y. Gao, W. Li, and K. Li, “Artificial Intelligence Security: Threats and Countermeasures,” ACM Computing Surveys, vol. 55, no. 1, 2021.

I. H. Sarker, M. H. Furhad, and R. Nowrozy, “AI-Driven Cybersecurity: An Overview, Security Intelligence Modeling and Research Directions,” SN Computer Science, vol. 2, no. 3, 2021.

M. Amrollahi, S. Hadayeghparast, H. Karimipour, F. Derakhshan, and G. Srivastava, “Enhancing network security via machine learning: Opportunities and challenges,” Handbook of Big Data Privacy, pp. 165–189, 2020.

F. Fourati and M.-S. Alouini, “Artificial intelligence for satellite communication: A review,” Intelligent and Converged Networks, vol. 2, no. 3, pp. 213–243, 2021.

O. Eigner, S. Eresheim, P. Kieseberg, L. D. Klausner, M. Pirker, T. Priebe, S. Tjoa, F. Marulli, and F. Mercaldo, “Towards resilient artificial intelligence: Survey and research issues,” Proceedings of the 2021 IEEE International Conference on Cyber

Security and Resilience, CSR 2021, pp. 536–542, 2021.

S. Zhou, C. Liu, D. Ye, T. Zhu,W. Zhou, and P. S. Yu, “Adversarial Attacks and Defenses in Deep Learning: From a Perspective

of Cybersecurity,” ACM Computing Surveys, vol. 55, no. 8, pp. 1–39, 2023.

A. Chakraborty, M. Alam, V. Dey, A. Chattopadhyay, and D. Mukhopadhyay, “A survey on adversarial attacks and defences,”

CAAI Transactions on Intelligence Technology, vol. 6, no. 1, pp. 25–45, 2021.

F. Aloraini, A. Javed, O. Rana, and P. Burnap, “Adversarial machine learning in IoT from an insider point of view,” Journal of

Information Security and Applications, vol. 70, 2022.

R. S. Sangwan, Y. Badr, and S. M. Srinivasan, “Cybersecurity for AI Systems: A Survey,” Journal of Cybersecurity and Privacy, vol. 3, pp. 166–190, May 2023.

A. Ayodeji, M. Mohamed, L. Li, A. Di Buono, I. Pierce, and H. Ahmed, “Cyber security in the nuclear industry: A closer look at digital control systems, networks and human factors,” Progress in Nuclear Energy, vol. 161, 2023.

S. Kaviani, K. J. Han, and I. Sohn, “Adversarial attacks and defenses on AI in medical imaging informatics: A survey,” Expert

Systems with Applications, vol. 198, 2022.

N. Kaloudi and L. I. Jingyue, “The AI-based cyber threat landscape: A survey,” ACM Computing Surveys, vol. 53, no. 1, 2020.

B. Guembe, A. Azeta, S. Misra, V. C. Osamor, L. Fernandez-Sanz, and V. Pospelova, “The Emerging Threat of Ai-driven

Cyber Attacks: A Review,” Applied Artificial Intelligence, vol. 36, Dec 2022.

T. C. Truong, Q. B. Diep, and I. Zelinka, “Artificial Intelligence in the Cyber Domain: Offense and Defense,” Symmetry, vol. 12, p. 410, Mar 2020.

L. Fritsch, A. Jaber, and A. Yazidi, “An Overview of Artificial Intelligence Used in Malware,” in Communications in Computer and Information Science, vol. 1650 CCIS, pp. 41–51, 2022.

L. Fritsch, A. Jaber, and A. Yazidi, “An Overview of Artificial Intelligence Used in Malware,” Communications in Computer and Information Science, vol. 1650 CCIS, pp. 41–51, 2022.

J. Chen, C. Su, and Z. Yan, “AI-Driven Cyber Security Analytics and Privacy Protection,” Security and Communication Networks, vol. 2019, 2019.

B. Murdoch, “Privacy and artificial intelligence: challenges for protecting health information in a new era,” BMC Medical Ethics, vol. 22, no. 1, 2021.

R. Blackman, “A Practical Guide to Building Ethical AI,” tech. rep., 2020.

V. Liagkou, C. Stylios, L. Pappa, and A. Petunin, “Challenges and opportunities in industry 4.0 for mechatronics, artificial intelligence and cybernetics,” Electronics (Switzerland), vol. 10, no. 16, 2021.

Thiyagarajan P., “A Review on Cyber Security Mechanisms Using Machine and Deep Learning Algorithms,” pp. 23–41, 2019.

CyberMaterial, “Symantec’s Targeted Attack Analytics Tool (TAA).”

T. M. Ghazal, M. K. Hasan, R. A. Zitar, N. A. Al-Dmour, W. T. Al-Sit, and S. Islam, “Cybers Security Analysis and Measurement Tools Using Machine Learning Approach,” 2022 1st International Conference on AI in Cybersecurity, ICAIC 2022, 2022.

N. Kshetri, “Economics of Artificial Intelligence in Cybersecurity,” IT Professional, vol. 23, no. 5, pp. 73–77, 2021.

I. Abusamrah, A. Madhoun, and S. Iseed, “Next-Generation Firewall, Deep Learning Endpoint Protection and Intelligent SIEM Integration,” 2021.

Sight and Sound Computers Limited, “Sophos Intercept X,” 2020.

K. Hamid, M. W. Iqbal, M. Aqeel, X. Liu, and M. Arif, “Analysis of Techniques for Detection and Removal of Zero-Day Attacks (ZDA),” pp. 248–262, 2023.

C. A. Teodorescu, “Perspectives and Reviews in the Development and Evolution of the Zero-Day Attacks,” Informatica Economica, vol. 26, no. 2/2022, pp. 46–56, 2022.

A. Kapoor, A. Gupta, R. Gupta, S. Tanwar, G. Sharma, and I. E. Davidson, “Ransomware detection, avoidance, and mitigation scheme: A review and future directions,” Sustainability (Switzerland), vol. 14, no. 1, 2022.

R. Das and R. Sandhane, “Artificial Intelligence in Cyber Security,” Journal of Physics: Conference Series, vol. 1964, no. 4, 2021.

D. Sasikala and K. Venkatesh Sharma, “Deployment of Artificial Intelligence with Bootstrapped Meta-Learning in Cyber Security,” Journal of Trends in Computer Science and Smart Technology, vol. 4, no. 3, pp. 139–152, 2022.

V. Dheap, “IBM QRadar Advisor with Watson: Revolutionizing the Way Security Analysts Work,” tech. rep., 2017.

G. Schram, “The Role of Artificial Intelligence in Cyber Operations: An Analysis of AI and Its Application to Malware-Based

Cyberattacks and Proactive Cybersecurity,” ProQuest Dissertations and Theses, p. 49, 2021.

M. Taddeo, “Three Ethical Challenges of Applications of Artificial Intelligence in Cybersecurity,” Minds and Machines, vol. 29, no. 2, pp. 187–191, 2019.

N. Yu, Z. Tuttle, C. J. Thurnau, and E. Mireku, “AI-powered GUI attack and its defensive methods,” ACMSE 2020 - Proceedings of the 2020 ACM Southeast Conference, pp. 79–86, 2020.

T. Terada, T. Sakamoto, Y. Kokubu, A. Yamatani, I. Takaesu, R. Inoue, T. Ozawa, and T. Isayama, “DeepLocker : AI-embedded attack,” tech. rep., 2020.

M. F. Ansari, B. Dash, P. Sharma, and N. Yathiraju, “The Impact and Limitations of Artificial Intelligence in Cybersecurity: A Literature Review,” Ijarcce, vol. 11, no. 9, 2022.

K. AL-Dosari, N. Fetais, and M. Kucukvar, “Artificial Intelligence and Cyber Defense System for Banking Industry: A Qualitative Study of AI Applications and Challenges,” Cybernetics and Systems, 2022.

M. Macas, C. Wu, and W. Fuertes, “A survey on deep learning for cybersecurity: Progress, challenges, and opportunities,”

Computer Networks, vol. 212, 2022.

Freepik, “Possible threats concerned with the emergence of AI,” 2020.

M. Malik, M. Kumar, V. Kumar, A. K. Gautam, S. Verma, S. Kumar, and D. Goyal, “High level browser security in cloud

computing services from cross site scripting attacks,” Journal of Discrete Mathematical Sciences and Cryptography, vol. 25,

no. 4, pp. 1073–1081, 2022.

P. J. Taylor, T. Dargahi, A. Dehghantanha, R. M. Parizi, and K. K. R. Choo, “A systematic literature review of blockchain cyber security,” Digital Communications and Networks, vol. 6, no. 2, pp. 147–156, 2020.

Businesswire, “Global Artificial Intelligence-Based Cybersecurity Market 2018-2022 — Increasing Vulnerability to Cyber-Threats to Boost Growth— Technavio,” tech. rep., 2018.

L. S. Nishad, R. Pandey, Akriti, S. Beniwal, J. Paliwal, and S. Kumar, “Security, privacy issues and challenges in cloud computing: A survey,” ACM International Conference Proceeding Series, vol. 04-05-Marc, 2016.

N. K. Singh, S. K. Pandey, M. Nagalakshmi, A. A. Kumar, M. Tiwari, and S. Kumar, “Artificial Intelligence-based cloud computing for Industry 5.0,” Proceedings - 2022 2nd International Conference on Innovative Sustainable Computational Technologies, CISCT 2022, 2022.

W. Ahmad, A. Rasool, A. R. Javed, T. Baker, and Z. Jalil, “Cyber security in IoT-based cloud computing: A comprehensive survey,” Electronics (Switzerland), vol. 11, no. 1, 2022.

A. Clim, “Cyber Security Beyond the Industry 4.0 Era. A Short Review on a Few Technological Promises,” Informatica Economica, vol. 23, no. 2/2019, pp. 34–44, 2019.

Z. Zhang, H. A. Hamadi, E. Damiani, C. Y. Yeun, and F. Taher, “Explainable Artificial Intelligence Applications in Cyber Security: State-of-the-Art in Research,” IEEE Access, vol. 10, pp. 93104–93139, 2022.

S. Kumar, B. Kumari, and A. Sharma, “A Purposed Approach from Artificial Intelligence Problems with 4 Problem Characteristics,” in Proceedings of the 12th INDIACom, pp. 4094–4096, 2018.

S. Kumar, P. Kumar, S. Pal Singh, and A. Saxena, “A New Approach for Providing Security Mechanism in Cloud with Possible Solutions and Results,” International Journal of Computer Applications, vol. 67, no. 12, pp. 30–33, 2013.

B. Dash, M. F. Ansari, P. Sharma, and A. Ali, “Threats and Opportunities with AI-based Cyber Security Intrusion Detection: A Review,” International Journal of Software Engineering & Applications, vol. 13, no. 5, pp. 13–21, 2022.

A. Razzaque, “Artificial Intelligence and IT Governance: A Literature Review,” Studies in Computational Intelligence, vol. 974, pp. 85–97, 2021.

P. Henman, “Improving public services using artificial intelligence: possibilities, pitfalls, governance,” Asia Pacific Journal of Public Administration, vol. 42, no. 4, pp. 209–221, 2020.

P. Robles and D. J. Mallinson, “Catching up with AI: Pushing toward a cohesive governance framework,” Politics and Policy, 2023.




How to Cite

S. Kumar, U. Gupta, A. K. Singh, and A. K. Singh, “Artificial Intelligence: Revolutionizing Cyber Security in the Digital Era”, J. Comput. Mech. Manag, vol. 2, no. 3, pp. 31–42, Aug. 2023.



Mini Reviews


Received 2023-07-06
Accepted 2023-07-29
Published 2023-08-31