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An improved chaotic image encryption algorithm using Hadoop-based MapReduce framework for massive remote sensed images in parallel IoT applications

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Abstract

Image encryption algorithms based on Chaotic approach are becoming increasingly popular for remotely sensed images using parallel techniques. It has been demonstrated that the most efficient image encryption algorithms are based on Chaos. Previous research using chaos-based cryptosystems has resulted in poor performance when using a single computer, compromising privacy, security, and reliability. Furthermore, there were issues when vulnerable satellite images were processed. This paper describes a novel chaos-based encryption technique that employs an external secret key and Henon, Logistic, and Gauss iterated maps. The proposed encryption algorithm is capable of efficiently encrypting a large number of images. When the number of images increases, however, these images become very small, and the technology becomes inefficient or impractical. This paper investigates the parallel method of image encryption on a large number of remotely sensed images in Hadoop. Hadoop's file visit method has been enhanced so that it can treat the entire Tiff file as a single unit. Furthermore, the file format is being extended to be supported by Hadoop in order to support GeoTiff in Hadoop. The results of the experiments show that the proposed parallel method for encryption is effective and scalable to a large number of images when compared to other well-known methods.

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Authors and Affiliations

  1. School of Information Technology, Skyline University College, University City Sharjah, 1797, Sharjah, UAE

    Mahmoud Ahmad Al-Khasawneh & Syed Atif Ali Shah

  2. Institute of Computing, Kohat University of Science and Technology, Kohat, 26000, Pakistan

    Irfan Uddin

  3. Faculty of Computer Sciences and Informatics, Amman Arab University, Amman, 11953, Jordan

    Ahmad M. Khasawneh & Laith Abualigah

  4. Department of Computer and Information Technology, Faculty of Applied Studies, King Abdulaziz University, Jidda, 21589, Saudi Arabia

    Marwan Mahmoud

  5. School of Electrical Engineering and Computer Science, National Uuniveristy of Science and Technlogy, Islamabad, Pakistan

    Syed Atif Ali Shah

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  1. Mahmoud Ahmad Al-Khasawneh
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  2. Irfan Uddin
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  4. Ahmad M. Khasawneh
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Contributions

MAA-K: conceptualization, and supervision. IU: experimental. SAAS: validation. AMK: methodology and draft writing. LA: review and cosupervision. MM: writing and editing.

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Correspondence to Ahmad M. Khasawneh.

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Al-Khasawneh, M.A., Uddin, I., Shah, S.A.A. et al. An improved chaotic image encryption algorithm using Hadoop-based MapReduce framework for massive remote sensed images in parallel IoT applications. Cluster Comput 25, 999–1013 (2022). https://doi.org/10.1007/s10586-021-03466-2

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