A MapReduce Based Approach for Secure Batch Satellite Image Encryption

Al-Khasawneh, M A, Faheem, Muhammad, Aldhahri, Eman A., Alzahrani, Abdulrahman and Alarood, Ala Abdulsalam (2023) A MapReduce Based Approach for Secure Batch Satellite Image Encryption. IEEE Access, 11. pp. 62865-62878. ISSN 2169-3536

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Abstract

The overarching goal of this research was to examine the state of satellite imagery security in relation to its deteriorating form due to rising demand. The most common approaches to safeguarding satellite images during transmission across transmission networks, which are not protected by standard encryption, are the focus of this investigation. Since satellite imagery can be encrypted both in transit and while stored on a computer’s hard drive, we put the suggested Image Encryption System to the test by applying it to a collection of satellite photos. Concurrently encrypting data and running MapReduce jobs is key to the study methodology employed. This will be carried out in the Hadoop ecosystem, where an innovative method of analysing random numbers for use in Image encryption will be put to the test. The encryption was processed using MapReduce in the Hadoop ecosystem. Images were saved as BMP files with added security metadata. The evaluation of experiments was based on four (4) indicators. It was found that the processing time for batch encryption calculations grew in proportion to the amount of computations. All cluster, map, and reduction processes were put to the test using encrypted images, exposing load balancing difficulties and inefficiencies. Histogram analysis, the basis of an image encryption technique, provides evidence that the encrypted pixel values are consistent. Therefore, compared to other methods, such as a histogram or information entropy, this one is superior. Because of how it was crafted, it can withstand even the most sophisticated attacks without being compromised.

Affiliation: Skyline University College
SUC Author(s): Al-Khasawneh, M A ORCID: https://orcid.org/0000-0003-1698-0237
All Author(s): Al-Khasawneh, M A, Faheem, Muhammad, Aldhahri, Eman A., Alzahrani, Abdulrahman and Alarood, Ala Abdulsalam
Item Type: Article
Subjects: B Information Technology > BD Big Data Analitics
B Information Technology > BW Computer Networks
Divisions: Skyline University College > School of IT
Depositing User: Mr Mosys Team
Date Deposited: 25 Dec 2023 13:43
Last Modified: 25 Dec 2023 13:43
URI: https://research.skylineuniversity.ac.ae/id/eprint/715
Publisher URL: https://doi.org/10.1109/ACCESS.2023.3279719
Publisher OA policy: https://v2.sherpa.ac.uk/id/publication/24685
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