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A novel True Random Bit Generator design for image encryption

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  • Etem, Taha
  • Kaya, Turgay

Abstract

Random Numbers are popular research topic due to the performance in encryption techniques. Owing to the protection of communication data against eavesdroppers, randomness is quiet important. The aim of this paper is to introduce an easily applicable True Random Bit Generator for image encryption. For this purpose, electromagnetic pollution is used as entropy source. Normalization procedure with very simple mathematical equations are applied on electric field strength values. Additionally, XOR post-processing procedure is performed. Different randomness test are studied for Random Numbers: NIST 800-22 Test Suite, Autocorrelation Test, Scale-Index Test. Subsequently, Tests are applied on normalized data and post-processed data separately. NIST Tests and Scale-Index Test are accomplished for both data, but Autocorrelation Test is successful for only Post-Processed values. Encryption of images are made with generated bits. This paper proves that, performing only NIST Tests are not trustworthy in True Random Bit Generators. High Frequency Electromagnetic Pollution firstly used as an entropy source in this work. Encryption process of sample images is concluded successfully.

Suggested Citation

  • Etem, Taha & Kaya, Turgay, 2020. "A novel True Random Bit Generator design for image encryption," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    • Handle: RePEc:eee:phsmap:v:540:y:2020:i:c:s0378437119315638
    DOI: 10.1016/j.physa.2019.122750
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    References listed on IDEAS

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    1. Hu, Yue & Liao, Xiaofeng & Wong, Kwok-wo & Zhou, Qing, 2009. "A true random number generator based on mouse movement and chaotic cryptography," Chaos, Solitons & Fractals, Elsevier, vol. 40(5), pages 2286-2293.
    2. González, C.M. & Larrondo, H.A. & Rosso, O.A., 2005. "Statistical complexity measure of pseudorandom bit generators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 354(C), pages 281-300.
    3. Larrondo, H.A. & González, C.M. & Martín, M.T. & Plastino, A. & Rosso, O.A., 2005. "Intensive statistical complexity measure of pseudorandom number generators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 356(1), pages 133-138.
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    Cited by:

    1. Kumar, Krishna & Roy, Satyabrata & Rawat, Umashankar & Malhotra, Shashwat, 2022. "IEHC: An efficient image encryption technique using hybrid chaotic map," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).

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