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Synchronization of chaotic artificial neurons and its application to secure image transmission under MQTT for IoT protocol

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Abstract

Artificial neurons are quite useful to generate chaotic behavior, and they can be implemented on embedded systems like Raspberry Pi that include WiFi network connectivity. In this manner, this paper shows the use of some artificial neurons to generate chaotic binary sequences whose randomness is enhanced by post-processing approaches and measured by performing statistical NIST SP 800-22 tests. The chaotic neurons are synchronized by different methods and each neuron is implemented on a Raspberry Pi, which allows connectivity to a machine-to-machine (M2M) broker. This wireless connectivity advantage is exploited herein to develop a lightweight cryptographic application under the message queueing telemetry transport (MQTT) for Internet of Things (IoT) protocol. The synchronized neurons have a topology in which one Raspberry Pi works as publisher and can send encrypted information to multiple subscribers. Due to the chaotic behavior of the neurons, the Raspberry Pi acting as subscriber can recover the encrypted information if and only if it has the right key, i.e., the correct random binary sequence generated by the publisher. To augment the security against attacks, the chaotic neurons have different initial conditions before M2M synchronization is accomplished, and the color image encryption under MQTT for IoT is evaluated by performing correlation, histogram, variance, entropy, and NPCR tests.

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Notes

  1. https://csrc.nist.gov/Projects/Random-Bit-Generation/Documentation-and-Software.

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Authors and Affiliations

  1. Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE), Luis Enrique Erro No. 1, Tonantzintla, 72840, Tonantzintla, Puebla, Mexico

    Astrid Maritza González-Zapata, Esteban Tlelo-Cuautle & Israel Cruz-Vega

  2. Purdue University, 401 N. Grant St., West Lafayette, IN, 47907, USA

    Walter Daniel León-Salas

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  1. Astrid Maritza González-Zapata
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  2. Esteban Tlelo-Cuautle
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  3. Israel Cruz-Vega
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  4. Walter Daniel León-Salas
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Correspondence to Esteban Tlelo-Cuautle.

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The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

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González-Zapata, A.M., Tlelo-Cuautle, E., Cruz-Vega, I. et al. Synchronization of chaotic artificial neurons and its application to secure image transmission under MQTT for IoT protocol. Nonlinear Dyn 104, 4581–4600 (2021). https://doi.org/10.1007/s11071-021-06532-x

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