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This paper models the interaction between a cryptographic defender choosing encryption algorithms and an attacker selecting cryptanalysis methods as a Stackelberg game. The defender randomizes over encryption algorithms (classical, post-quantum, or hybrid) to balance security and cost, while the attacker optimizes cryptanalysis strategies based on the defender's choice and resource constraints. The authors propose a dynamic programming approach to solve the attacker's optimization problem and formulate the defender's Stackelberg optimization as a linear program.
Optimizing cryptographic defenses against resource-constrained attackers is now tractable via a Stackelberg game formulation solvable with dynamic programming and linear programming.
Similar to a strategic interaction between rational and intelligent agents, cryptography problems can be examined through the prism of game theory. In this setting, the agent aiming to protect a message is called the defender, while the one attempting to decrypt it, generally for malicious purposes, is the attacker. To strengthen security in cryptography, various strategies have been developed, among which hybridization stands out as a key concept in modern cryptographic design. This strategy allows the defender to select among different encryption algorithms (classical, post-quantum, or hybrid) while carefully balancing security and operational costs. On the other side, the attacker, limited by available resources, chooses cryptanalysis methods capable of breaching the selected algorithm. We model this interaction as a Stackelberg cryptographic hybridization problem under resource constraints. Here, the defender randomizes over encryption algorithms, and the attacker observes the choice before selecting suitable cryptanalysis methods. The attacker's decision is framed as a conditional optimization problem, which we refer to as the ``attacker subgame''. We then propose a dynamic programming approach for the attacker's subgame, while the defender's Stackelberg optimization is formulated as a linear program.