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An Encryption Scheme Based on Grain Stream Cipher and Chaos for Privacy Protection of Image Data on IoT Network

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Abstract

IoT-enabled devices can collect information and act based on instructions over the Internet; they can sometimes communicate device to device. The IoT devices are mainly sensors that collect data and transmit over the internet to some base station or servers using a wireless medium like Bluetooth, Wi-Fi, etc. The transmitted data goes through multiple hierarchies of devices which makes it vulnerable to different attacks and data leaks which may cost the user badly. To resist these threats, a proper encryption scheme is required. A lightweight encryption (LWE) scheme is proposed in this paper for secure IoT devices using a piecewise linear chaotic map (PWLCM) and a Grain keystream generator (GKSG). It takes a plain image (PI) as input and scrambles the pixels-by-bit plain manipulation followed by XOR operation among the scrambled pixel values using pseudorandom number sequence (PRNS) generated by the PWLCM and GKSG. The test results show that the proposed method is secure and optimistic.

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References

  1. Basha, S. M., Mathivanan, P., & Ganesh, A. B. (2022). Bit level color image encryption using logistic-sine-tent-chebyshev (lstc) map. Optik, pp. 168956.

  2. Dabov, K., Foi, A., Katkovnik, V., & Egiazarian, K. (2007). Image denoising by sparse 3-d transform-domain collaborative filtering. IEEE Transactions on Image Processing, 16(8), 2080–2095.

    Article  MathSciNet  Google Scholar 

  3. Deb, S., & Bhuyan, B. (2021). Chaos-based medical image encryption scheme using special nonlinear filtering function based lfsr. Multimedia Tools and Applications, 80(13), 19803–19826.

    Article  Google Scholar 

  4. Ding, D., Xiao, H., Yang, Z., Luo, H., Hu, Y., Zhang, X., & Liu, Y. (2022). Coexisting multi-stability of hopfield neural network based on coupled fractional-order locally active memristor and its application in image encryption. Nonlinear Dynamics, pp. 1–26.

  5. Gao, X., Mou, J., Xiong, L., Sha, Y., Yan, H., & Cao, Y. (2022). A fast and efficient multiple images encryption based on single-channel encryption and chaotic system. Nonlinear Dynamics, pp. 1–24.

  6. Ghazvini, M., Mirzadi, M., & Parvar, N. (2020). A modified method for image encryption based on chaotic map and genetic algorithm. Multimedia Tools and Applications, 79(37), 26927–26950.

    Article  Google Scholar 

  7. Ghorbania, A., Saberikamarposhti, M., & Yadollahi, M. (2022). Using ribonucleic acid (rna) and hénon map in new image encryption scheme. Optik, pp. 168961.

  8. Gu, K., Wang, S., Zhai, G., Ma, S., Yang, X., & Zhang, W. (2016). Content-weighted mean-squared error for quality assessment of compressed images. Signal, Image and Video Processing, 10(5), 803–810.

    Article  Google Scholar 

  9. Hedayati, R., & Mostafavi, S. (2022). A lightweight image encryption algorithm for secure communications in multimedia internet of things. Wireless Personal Communications, 123(2), 1121–1143.

    Article  Google Scholar 

  10. Jain, K., Aji, A., & Krishnan, P. (2021). Medical image encryption scheme using multiple chaotic maps. Pattern Recognition Letters, 152, 356–364.

    Article  Google Scholar 

  11. Kamble, V. M., Parlewar, P., Keskar, A. G., & Bhurchandi, K. M. (2016). Performance evaluation of wavelet, ridgelet, curvelet and contourlet transforms based techniques for digital image denoising. Artificial Intelligence Review, 45(4), 509–533.

    Article  Google Scholar 

  12. Kamrani, A., Zenkouar, K., & Najah, S. (2020). A new set of image encryption algorithms based on discrete orthogonal moments and chaos theory. Multimedia Tools and Applications, 79(27), 20263–20279.

    Article  Google Scholar 

  13. Kandar, S., Chaudhuri, D., Bhattacharjee, A., & Dhara, B. C. (2019). Image encryption using sequence generated by cyclic group. Journal of Information Security and Applications, 44, 117–129.

    Article  Google Scholar 

  14. Kari, A. P., Navin, A. H., Bidgoli, A. M., & Mirnia, M. (2021). A new image encryption scheme based on hybrid chaotic maps. Multimedia Tools and Application, 80(2), 2753–2772.

    Article  Google Scholar 

  15. Li, F., Wu, H., Zhou, G., & Wei, W. (2019). Robust real-time image encryption with aperiodic chaotic map and random-cycling bit shift. Journal of Real-Time Image Processing, 16(3), 775–790.

    Article  Google Scholar 

  16. Li, Y., Wang, C., & Chen, H. (2017). A hyper-chaos-based image encryption algorithm using pixel-level permutation and bit-level permutation. Optics and Lasers in Engineering, 90, 238–246.

    Article  Google Scholar 

  17. Massey, J., & Liu, R.-W. (1964). Equivalence of nonlinear shift-registers. IEEE Transactions on Information Theory, 10(4), 378–379.

    Article  MATH  Google Scholar 

  18. Mondal, B. (2018). Cryptographic image scrambling techniques. In: Cryptographic and Information Security (pp. 37–65). CRC Press.

  19. Mondal, B., Kumar, P., & Singh, S. (2018). A chaotic permutation and diffusion based image encryption algorithm for secure communications. Multimedia Tools and Applications, 77(23), 31177–31198.

    Article  Google Scholar 

  20. Mondal, B., Mandal, T., Khan, D. A., & Choudhury, T. (2018). A secure image encryption scheme using chaos and wavelet transformations. Recent Patents on Engineering, 12(1), 5–14.

    Article  Google Scholar 

  21. Mondal, B., Mandal, T., Kumar, P., & Biswas, N. (2017). A secure partial encryption scheme based on bit plane manipulation. In: 2017 7th International Symposium on Embedded Computing and System Design (ISED) (pp. 1–5). IEEE .

  22. Mondal B., & Singh, J.P. (2022). A lightweight image encryption scheme based on chaos and diffusion circuit. Multimedia Tools and Applications, 1–25.

  23. Musanna, F., Dangwal, D., & Kumar, S. (2021). Novel image encryption algorithm using fractional chaos and cellular neural network. Journal of Ambient Intelligence and Humanized Computing, 1–22.

  24. Nan, S.-X., Feng, X.-F., Wu, Y.-F., & Zhang, H. (2022). Remote sensing image compression and encryption based on block compressive sensing and 2d-lcccm. Nonlinear Dynamics, 1–25.

  25. Qiu, H., Qiu, M., Liu, M., & Ming, Z. (2019). Lightweight selective encryption for social data protection based on ebcot coding. IEEE Transactions on Computational Social Systems, 7(1), 205–214.

    Article  Google Scholar 

  26. Shah, A. A., Parah, S. A., Rashid, M., & Elhoseny, M. (2020). Efficient image encryption scheme based on generalized logistic map for real time image processing. Journal of Real-Time Image Processing, 17(6), 2139–2151.

    Article  Google Scholar 

  27. Sneha, P., Sankar, S., & Kumar, A. S. (2020). A chaotic colour image encryption scheme combining walsh-hadamard transform and arnold-tent maps. Journal of Ambient Intelligence and Humanized Computing, 11(3), 1289–1308.

    Article  Google Scholar 

  28. Song, W., Fu, C., Tie, M., Sham, C.-W., Liu, J., & Ma, H.-F. (2022). A fast parallel batch image encryption algorithm using intrinsic properties of chaos. Signal Processing: Image Communication, 102, 116628.

    Google Scholar 

  29. Suman, R. R., Mondal, B., & Mandal,T. (2022). A secure encryption scheme using a composite logistic sine map (clsm) and sha-256. Multimedia Tools and Applications, 1–22.

  30. Suman, R. R., Mondal, B., & Mandal, T. (2022). Security trend and trust in india’s e-governance framework. Journal of Electronic Government Research (IJEGR), 18(1), 1–16.

    Article  Google Scholar 

  31. Suman, R. R., Mondal, B., Singh, S. K., & Mandal, T. (2021). A secure color image encryption scheme based on chaos. In: Machine Vision and Augmented Intelligence-Theory and Applications, (pp. 365–375). Springer.

  32. Talhaoui, M., Wang, X., & Midoun, M. (2020). Fast image encryption algorithm with high security level using the bülban chaotic map. Journal of Real-Time Image Processing, 18, 85–98.

    Article  Google Scholar 

  33. Tiwari, D., Mondal, B., Singh, S. K., & Koundal,D. (2022). Lightweight encryption for privacy protection of data transmission in cyber physical systems. Cluster Computing, 1–15.

  34. Toktas A., & Erkan, U. (2021). 2d fully chaotic map for image encryption constructed through a quadruple-objective optimization via artificial bee colony algorithm. Neural. Comput. Appl., pages 1–25.

  35. Wang, W., Si, M., Pang, Y., Ran, P., Wang, H., Jiang, X., Liu, Y., Wu, J., Wu, W., Chilamkurti, N., et al. (2018). An encryption algorithm based on combined chaos in body area networks. Computers and Electrical Engineering, 65, 282–291.

    Article  Google Scholar 

  36. Wang, X., & Du, X. (2022). Pixel-level and bit-level image encryption method based on logistic-chebyshev dynamic coupled map lattices. Chaos, Solitons & Fractals, 155, 111629.

    Article  MathSciNet  Google Scholar 

  37. Wang, X., Guan, N., & Liu, P. (2022). A selective image encryption algorithm based on a chaotic model using modular sine arithmetic. Optik, 258, 168955.

    Article  Google Scholar 

  38. Yahi, A., Bekkouche, T., Daachi, M. E. H., & Diffellah, N. (2022). A color image encryption scheme based on 1d cubic map. Optik, 249, 168290.

    Article  Google Scholar 

  39. Zahmoul, R., Ejbali, R., & Zaied, M. (2017). Image encryption based on new beta chaotic maps. Optics and Lasers in Engineering, 96, 39–49.

    Article  Google Scholar 

  40. Zheng, J., & Zeng, Q. (2022). An image encryption algorithm using a dynamic s-box and chaotic maps. Applied Intelligence, 1–15.

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The authors hereby declare that there was no full or partial financial support from any organization.

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  1. Department of Computer Science and Engineering, National Institute of Technology Patna, Patna, 800005, India

    Punam Kumari & Bhaskar Mondal

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  1. Punam Kumari
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  2. Bhaskar Mondal
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Correspondence to Bhaskar Mondal.

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Kumari, P., Mondal, B. An Encryption Scheme Based on Grain Stream Cipher and Chaos for Privacy Protection of Image Data on IoT Network. Wireless Pers Commun 130, 2261–2280 (2023). https://doi.org/10.1007/s11277-023-10382-8

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