A Stackelberg Model for Hybridization in Cryptography
Willie Kouam, Stefan Rass, Zahra Seyedi, Shahzad Ahmad, Eckhard Pfluegel
TLDR
This paper models cryptographic hybridization as a Stackelberg game, where a defender chooses encryption and an attacker responds with cryptanalysis.
Key contributions
- Models cryptographic hybridization as a Stackelberg game between a defender and an attacker.
- Defender randomizes over encryption algorithms, balancing security and operational costs.
- Attacker's response is a conditional optimization problem, solved via dynamic programming.
Why it matters
This work provides a novel game-theoretic framework for designing more robust cryptographic systems. By modeling the strategic interaction between defenders and attackers, it offers insights into optimal hybridization strategies. This can lead to stronger security against evolving threats, including post-quantum attacks.
Original Abstract
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.
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