Combinatorial game theory applications in cryptographic protocols
Mahadev Kalyanrao Patilpatilmahadevk@gmail.comSchool of Computer Science & Engineering (SoCSE)RV UniversityBengaluru, Karnataka, 560059, IndiaView full profile → , *Archana ChauguleCorresponding authorarchana.chaugule@pccoer.inDepartment of Computer EngineeringPCET’S Pimpri Chinchwad College of Engineering & ResearchRavet, Pune, Maharashtra, 412101, IndiaView full profile → , Snehal Swapnil Jawahiresnehal.jawahire@vit.eduDepartment of Computer EngineeringVishwakarma Institute of TechnologyPune, Maharashtra, 411037, IndiaView full profile → , Varsha Kiran Patilvarsha.patil@aissmsioit.orgDepartment of Electronics & Telecommunication EngineeringAISSMS Institute of Information TechnologyPune, Maharashtra, 411001, IndiaView full profile → , Aparna Shrinivas Shirkandekaleaparna5@gmail.comDepartment of Electronics & Telecommunication EngineeringS. B. Patil College of EngineeringIndapur, Pune, Maharashtra, 413106, IndiaView full profile → , Neeraj Guptaneeraj.gupta@gla.ac.inDepartment of Computer Engineering & ApplicationsGLA UniversityMathura, Uttar Pradesh, 281406, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 01 Apr 2026
- Published Online:
- 31 Oct 2026
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JDMSC-3076
- Pages:
- 4595–4610
Abstract
These growing intricacy of cyber threats and the fast growth of interconnected digital systems have revealed the weaknesses of traditional cryptographic protocols basing their operation on fixed mathematical assumptions. The contemporary security landscapes require dynamic, intelligent and durable systems that can counter the dynamic adversarial behavior. Here, the paper discusses how combinatorics game theory can be applied to the design of cryptographic protocols to increase their effectiveness in providing better security and flexibility in their usage. The main goal of this work consists in creation of a new cryptographic framework in the form of combinatorial game which will represent the process of encryption and key generation as the strategies of the defender and adversary. The suggested methodology utilizes combinatorial frameworks, e.g., permutation spaces, transitions of the game states, and game-theoretic techniques, e.g., strategy optimization, and the minimax formulation, and equilibrium analysis. The mechanism of key generation is dynamic based on optimal game strategies and the process of encryption and decryption is motivated by the use of permutation based transformations and functions based on the strategies. There is also a feedback loop to enhance the continuous evolution of keys that the framework considers, and it enhances its flexibility and resistance to new threats. Measures that are used to perform the performance evaluation include encryption/decryption time, key space size, computational overhead and security strength. The findings show that the suggested model can attain a high degree of security with entropy being higher than what is available in the conventional schemes, with reasonable computational efficiency. The comparison to AES, RSA, and ECC shows that the given approach is more flexible, has a greater key space, and resistance to brute-force and analytical attacks. In general, this paper provides a strong and scalable cryptographic paradigm that could be used in the next-generation secure communication systems.
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References
[1] R. Verma, S. Koul, K. V. Ajaygopal, and S. Singh, “Exploring Game Theoretic Applications in Cyber Security,” 2024 International Conference on Intelligent Systems for Cybersecurity (ISCS), Gurugram, India, pp. 1-6 (2024), doi: 10.1109/ISCS61804.2024.10581244.
[2] M. Antunes, M. Maximiano, R. Gomes, and D. Pinto, “Information security and cybersecurity management: A case study with SMEs in Portugal,” J. Cybersecur. Priv., vol. 1, no. 2, pp. 219–238 (2021).
[3] A. Bandyopadhyay, N. Qadir, and S. Malik, “Quantum game theory-based cloud resource allocation,” IEEE Access, vol. 13, pp. 1–15 (2025).
[4] A. Natarajan and T. Zhang, “Bounding the Quantum Value of Compiled Nonlocal Games: From CHSH to BQP Verification,” 2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS), Santa Cruz, CA, USA, pp. 1342-1348 (2032), doi: 10.1109/FOCS57990.2023.00081.
[5] M. I. Huilgol and S. Asok, “PBIB-designs with constant block sums arising from different graph parameters,” J. Discrete Math. Sci. Cryptogr., vol. 28, no. 7, pp. 2697–2721 (2025), doi: 10.47974/JDMSC-2064.
[6] A. Duchêne, M. Rigo, and J. Shallit, “Automatic proofs in combinatorial game theory,” J. Comb. Optim., vol. 48 (2025).
[7] A. Ikramov, “On retrieval of secret key parameters from symmetric block cipher O’zDST 1105:2009 using modified SQUARE cryptanalysis,” J. Discrete Math. Sci. Cryptogr., vol. 28, no. 6, pp. 2309–2322 (2025), doi: 10.47974/JDMSC-2230.
[8] J. S. Huh and K. Kandasamy, “Nash incentive-compatible online mechanism learning via weakly differentially private learning,” in Proc. Int. Conf. Mach. Learn. (ICML) (2024).
[9] M. A. Huggan and R. J. Nowakowski, “Cheating robot games,” Int. J. Game Theory, vol. 53, pp. 1145–1167 (2024).
[10] K. Ito, “Cryptoeconomics and tokenomics as economics: A survey with opinions,” arXiv preprint arXiv:2407.15715 (2024).
[11] P. Prabu, M. Alsulami, D. Alsadie, A. K. J. Saudagar, M. Alkhathami, and R. C. Poonia, “Utilizing behavioral deep learning models to monitoar and alert physicians regarding trauma cases,” J. Inf. Optim. Sci., vol. 44, no. 5, pp. 983–995 (2023), doi: 10.47974/JIOS-1461.
[12] M. W. Nkongolo, “Gamified Security Tactics Through Digital Card Game Models,” 2024 4th International Multidisciplinary Information Technology and Engineering Conference (IMITEC), Vanderbijlpark, South Africa, pp. 48-55 (2024), doi: 10.1109/IMITEC60221.2024.10850994.
[13] A. N. Kulkarni, M. S. Cohen, and J. Fu, “Integrated resource allocation and strategy synthesis in safety games on graphs with deception,” arXiv preprint arXiv:2407.14436 (2024).
[14] G. Jeong, N. Lee, J. Kim, and H. Oh, “Azeroth: Auditable Zero-Knowledge Transactions in Smart Contracts,” in IEEE Access, vol. 11, pp. 56463-56480 (2023), doi: 10.1109/ACCESS.2023.3279408.




