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Coati optimization algorithm to recover the secret key of the classical transposition cryptosystem.
Ashish Jain1, Inderjeet Kaur2, Divya Gautam3
1Department of Computer Science and Engineering, Institute of Engineering and Technology, JK Lakshmipat University, Jaipur, India.
Scientific Reports
|July 2, 2026
Summary
This study enhances classical transposition cryptosystem key recovery using the coati optimization algorithm. The novel approach demonstrates competitive performance against established metaheuristics, improving cryptanalysis accuracy and efficiency.
Area of Science:
- Computer Science
- Cryptography
- Artificial Intelligence
Background:
- Classical transposition cryptosystems are a foundational element in historical cryptography.
- Key recovery is crucial for assessing and strengthening cryptographic security.
- Metaheuristic algorithms offer powerful tools for complex optimization problems in cryptanalysis.
Purpose of the Study:
- To introduce and evaluate an enhanced cryptanalysis approach for classical transposition ciphers.
- To adapt the coati optimization algorithm for the specific task of secret key recovery.
- To benchmark the proposed method against existing metaheuristic techniques.
Main Methods:
- Customization of the coati optimization algorithm's framework for transposition cryptanalysis.
- Implementation of the tailored coati optimization algorithm to recover secret keys.
- Comparative analysis against genetic algorithm, cuckoo search, and particle swarm optimization.
Main Results:
- The proposed coati optimization algorithm-based method shows competitive performance in key recovery.
- The enhanced approach frequently outperforms genetic algorithm, cuckoo search, and particle swarm optimization.
- Evaluation metrics include accuracy, effectiveness, and efficiency of the cryptanalysis.
Conclusions:
- The coati optimization algorithm provides a promising and effective tool for classical transposition cryptosystem key recovery.
- The tailored approach offers a significant advancement over existing metaheuristic methods for this specific cryptanalysis task.
- Future work should explore the framework's applicability to multilingual cryptanalysis and diverse ciphertext types.
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