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Implementing a Chaotic Cryptosystem by Performing Parallel Computing on Embedded Systems with Multiprocessors.

Abraham Flores-VergaraEverardo Inzunza-GonzálezEnrique Efrén García-GuerreroOscar Roberto López-BonillaEduardo Rodríguez-OrozcoJuan Miguel Hernández-OntiverosJosé Ricardo Cárdenas-ValdezEsteban Tlelo-Cuautle
Published in: Entropy (Basel, Switzerland) (2019)
Profiling and parallel computing techniques in a cluster of six embedded systems with multiprocessors are introduced herein to implement a chaotic cryptosystem for digital color images. The proposed encryption method is based on stream encryption using a pseudo-random number generator with high-precision arithmetic and data processing in parallel with collective communication. The profiling and parallel computing techniques allow discovery of the optimal number of processors that are necessary to improve the efficiency of the cryptosystem. That is, the processing speed improves the time for generating chaotic sequences and execution of the encryption algorithm. In addition, the high numerical precision reduces the digital degradation in a chaotic system and increases the security levels of the cryptosystem. The security analysis confirms that the proposed cryptosystem is secure and robust against different attacks that have been widely reported in the literature. Accordingly, we highlight that the proposed encryption method is potentially feasible to be implemented in practical applications, such as modern telecommunication devices employing multiprocessors, e.g., smart phones, tablets, and in any embedded system with multi-core hardware.
Keyphrases
  • deep learning
  • systematic review
  • single cell
  • machine learning
  • electronic health record
  • convolutional neural network
  • big data
  • public health