BREAKING A SC-CNN-BASED CHAOTIC MASKING SECURE COMMUNICATION SYSTEM
| Autor: | Gerardo Pastor, Ab. Orue, Miguel Romera, Carmen Sanchez-Avila, Gonzalo Alvarez, Veronica Fernandez, Fausto Montoya, Shujun Li |
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| Rok vydání: | 2009 |
| Předmět: |
Theoretical computer science
Computer science Applied Mathematics Key space Transmitter Plaintext Data_CODINGANDINFORMATIONTHEORY law.invention Cryptanalysis law Modeling and Simulation Cellular neural network Computer Science::Multimedia Ciphertext Chua’s attractor State (computer science) Chaotic masking Engineering (miscellaneous) Algorithm Decoding methods Computer Science::Information Theory Computer Science::Cryptography and Security |
| Zdroj: | Digital.CSIC. Repositorio Institucional del CSIC instname |
| ISSN: | 1793-6551 0218-1274 |
| DOI: | 10.1142/s0218127409023652 |
| Popis: | This paper studies the security of a chaotic cryptosystem based on Chua’s circuit and implemented with State Controlled Cellular Neural Networks (SC-CNN). Here we prove that the plaintext can be retrieved by bandpass filtering of the ciphertext or by using an imperfect decoder with wrong receiver parameters. In addition we find that the key space of the system can be reduced notably, and the required resolution of the parameter values to recover a meaningful plaintext is as coarse as 5%, easing a brute-force attack. The system parameters can be determined with high precision through the analysis of the decoding error produced by the mismatch between the parameters of receiver and transmitter. |
| Databáze: | OpenAIRE |
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