An Image Encryption Method Based on Lorenz Chaotic Map and Hunter-Prey Optimization

DOI:

https://doi.org/10.36371/port.2023.4.3

Authors

  • Qutaiba K. Abed Informatics Institute for Postgraduate Studies, Iraqi Commission for Computers and Informatics, Baghdad, Iraq
  • Waleed A. Mahmoud Al-Jawher College Engineering, Uruk University, Baghdad, Iraq.

Through the development of communication technology, fast and efficient tools are required to practically secure the process of data exchange in securing images. This paper presents a new method of encryption for protecting images against many attacks from unsafe public networks. Lorenz chaos map is used to generate a sequence of random numbers for each stage depending on the initial parameters. The Hunter Prey optimization algorithm is applied in order to obtain these parameters to use them based on the original image. Therefore, the random sequence number generated by the Lorenz chaotic map will be different from one image to another. That will make it unpredictable and very difficult to discover the process of encryption. The results of simulation experiments demonstrate that the encryption algorithm have passed the plaintext sensitivity test with the NPCR of 0.99785 and the UACI of 0.33623. As well as the correlation coefficient test values in the three directions gave the values of (v = -0.0007, h = -0.0000, d = 0.0005). Also, the calculated information entropy test value was 7.9983. These results demonstrate that this algorithm is very strong enough to withstand the various types of attacks that images can be exposed during transmission on the Internet or any public network. The security analysis's comparison of the proposed changes to similar ones revealed that the proposed encryption system is more efficient.

Keywords:

Hunter pray algorithm, , Image encryption, Lorenz chaotic map, Parameter adjustment

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Abed, Q. K. ., & Al-Jawher, W. A. M. . (2023). An Image Encryption Method Based on Lorenz Chaotic Map and Hunter-Prey Optimization. Journal Port Science Research, 6(4), 332–343. https://doi.org/10.36371/port.2023.4.3

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