Article · Journal of Intelligent Systems · January 1, 2026
Ciphertext-only classification of encryption algorithms using deep learning
Zhanna Alimzhanova, Malik Zharykov, Salamat Zhunusbayeva, Гульнара Тулешева, Gulzhazira Smatova
Abstract
Abstract This study presents a machine learning approach for identifying encryption algorithms based solely on ciphertext analysis. The problem is formulated as a supervised classification task, where features are learned directly from ciphertext samples generated by four widely used symmetric encryption algorithms. Experimental results show that the model can reliably distinguish between ciphers under constrained conditions, particularly when initialization vectors (IVs) and key distributions remain consistent across samples. These findings indicate that ciphertexts retain subtle statistical patterns that can be exploited for algorithm identification, while also highlighting limitations in generalization under distribution shifts.
Related publications
- MODIFIED IMAGE ENCRYPTION ALGORITHM BASED ON CHAOTIC DYNAMICS2026 · Shared topic: Cryptographic Implementations and Security
- HYBRID ENCRYPTION ARCHITECTURE BASED ON CHAOTIC DYNAMICS AND AES-GCM ALGORITHM FOR PROTECTING MULTIMEDIA DATAКазУТБ · 2026 · Shared topic: Cryptographic Implementations and Security
- LIGHTWEIGHT CRYPTO SYSTEM BASED ON DFA AND LORENZ CHAOS FOR SECURE DATA TRANSFER IN IOT ON MICROCONTROLLERSКазУТБ · 2025 · Shared topic: Cryptographic Implementations and Security
- Hybrid DFA-Chaos Cryptosystem for Secure IoT Data Transmission on Resource-Constrained DevicesInternational Journal of Innovative Research and Scientific Studies · 2025 · Shared topic: Cryptographic Implementations and Security