Current - Issue
Original Article
RED: Resilient Environment for Defense Testing: An AI-Driven Adaptive Red Team Evaluation Framework
Dr. B. M. Vidyavathi1
M. Akhil Sai2
M. Jahnavi3
M. Yashashwini Sai4
Maarif Maniyar5
1 Professor, Department of Artificial Intelligence and Machine Learning, Ballari Institute of Technology and Management, Bengaluru, Karnataka, India. 2 3 4 5 Student Department of Artificial Intelligence and Machine Learning, Ballari Institute of Technology and Management, Bengaluru, Karnataka, India.
Published Online: May-June 2026
Pages: 151-154
Cite this article
↗ https://www.doi.org/10.59256/ijsreat.20260603021
References
1. S. H. Oh, J. Kim, and J. Park, ‘Dynamic Cyberattack Simulation: Integrating Improved Deep Reinforcement Learning with the MITRE
ATT&CK Framework,’ Sensors, Vol. 25, No. 13, 2025.
2. H. Rauf, M. Usama, F. Ali, and S. Iqbal, ‘Using Generative AI for Simulating Cyber Security Attacks and Defense Mechanisms,’ Wireless
Sensor Network, Vol. 17, 2024.
3. M. A. I. Mallick and R. Nath, ‘Simulating Cyber Threats: A Review of AI-powered Attack Simulators,’ Smart Energy and Sustainability,
Vol. 3, No. 2, 2025.
4. Y. Gao, ‘Cyber Attacks and Defense: AI Driven Approaches and Techniques,’ Electronics, Vol. 13, No. 15, 2024.
5. G. Apruzzese, M. Colajanni, and M. Marchetti, ‘Evaluating Cybersecurity Education and Training through Cyber Ranges,’ IEEE Security
& Privacy, Vol. 16, No. 6, 2018.
6. Y. Zhang, L. Wang, and T. Zhu, ‘Reinforcement Learning Based Attack Path Discovery in Network Security,’ IEEE Access, Vol. 8, 2020.
7. R. Mall, Software Project Management: Principles and Practices, Pearson Education, 2014.
8. I. Sommerville, Software Engineering: Concepts and Applications, Pearson Education, 2011.
9. R. S. Sutton and A. G. Barto, Reinforcement Learning: An Introduction, 2nd ed. Cambridge, MA, USA: MIT Press, 2018.
10. C. J. C. H. Watkins and P. Dayan, ‘Q-learning,’ Machine Learning, Vol. 8, No. 3–4, pp. 279–292, 1992
ATT&CK Framework,’ Sensors, Vol. 25, No. 13, 2025.
2. H. Rauf, M. Usama, F. Ali, and S. Iqbal, ‘Using Generative AI for Simulating Cyber Security Attacks and Defense Mechanisms,’ Wireless
Sensor Network, Vol. 17, 2024.
3. M. A. I. Mallick and R. Nath, ‘Simulating Cyber Threats: A Review of AI-powered Attack Simulators,’ Smart Energy and Sustainability,
Vol. 3, No. 2, 2025.
4. Y. Gao, ‘Cyber Attacks and Defense: AI Driven Approaches and Techniques,’ Electronics, Vol. 13, No. 15, 2024.
5. G. Apruzzese, M. Colajanni, and M. Marchetti, ‘Evaluating Cybersecurity Education and Training through Cyber Ranges,’ IEEE Security
& Privacy, Vol. 16, No. 6, 2018.
6. Y. Zhang, L. Wang, and T. Zhu, ‘Reinforcement Learning Based Attack Path Discovery in Network Security,’ IEEE Access, Vol. 8, 2020.
7. R. Mall, Software Project Management: Principles and Practices, Pearson Education, 2014.
8. I. Sommerville, Software Engineering: Concepts and Applications, Pearson Education, 2011.
9. R. S. Sutton and A. G. Barto, Reinforcement Learning: An Introduction, 2nd ed. Cambridge, MA, USA: MIT Press, 2018.
10. C. J. C. H. Watkins and P. Dayan, ‘Q-learning,’ Machine Learning, Vol. 8, No. 3–4, pp. 279–292, 1992
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