Advertisement

Optimal Stream Encryption for Multiple Shares of Images by Improved Cuckoo Search Model

  • K. ShankarEmail author
  • Mohamed Elhoseny
Chapter
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 564)

Abstract

Security of the media information such as image and video is one of the fundamental prerequisites for broadcasting communications and computer systems. Most of image security system, for famous systems, similar to the Internet, is not reasonable for wireless sensor systems, requesting legitimate examination around there. In the proposed investigation, the security of Digital Images (DI) is upgraded by utilizing a Lightweight encryption algorithm. To ensure security, the images selected for security investigation was shared by a number of copies. With the help of the presented share creation model, for example, Chinese Remainder Theorem (CRT), the image was encoded into a number of shares and the created shares were highly secured by the proposed Stream Encryption (SE) algorithm. The metaheuristic algorithm was introduced by passing the selection of optimal public and private keys to encrypt as well as decrypt the image in secure transmission. With the help of Improved Cuckoo Search Algorithm (ICSA), the optimal keys were selected with fitness function as maximum throughput. The proposed SE-based ICSA algorithm consumed the least time in creating key value to decrypt the image in WSN security model. The simulation result exhibited that the SE-based ICSA algorithm enhanced the exactness of DI security for all input images (Lena, Barbara, baboon, house, and airplane) when compared with existing algorithms.

Keywords

Image security Share creation Lightweight SE Key optimization ICSA Throughput PSNR WSN 

References

  1. 1.
    Patel, T., & Srivastava, R. (2016, August). A new technique for color share generation using visual cryptography. In International Conference on Inventive Computation Technologies (ICICT) (Vol. 2, pp. 1–4). IEEE. Google Scholar
  2. 2.
    Khokhar, P., & Jena, D. (2017). Color image visual cryptography scheme with enhanced security. In Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications (pp. 267–279). Singapore: Springer.Google Scholar
  3. 3.
    Avudaiappan, T., Balasubramanian, R., Pandiyan, S. S., Saravanan, M., Lakshmanaprabu, S. K., & Shankar, K. (2018). Medical image security using dual encryption with the oppositional based optimization algorithm. Journal of Medical Systems, 42(11), 208.CrossRefGoogle Scholar
  4. 4.
    Gupta, M., & Chauhan, D. (2015). A visual cryptographic scheme to secure image shares using digital watermarking. International Journal of Computer Science and Information Technologies (IJCSIT). Google Scholar
  5. 5.
    Shinde, K. V., Kaur, H., & Patil, P. (2015, February). Enhance security for spontaneous wireless ad hoc network creation. In 2015 International Conference on Computing Communication Control and Automation (ICCUBEA) (pp. 247–250). IEEE.Google Scholar
  6. 6.
    Elhoseny, M., & Hassanien, A. E. (2019). Dynamic wireless sensor networks: New directions for smart technologies. Published in Studies in Systems, Decision and Control. Springer.Google Scholar
  7. 7.
    Shankar, K., & Eswaran, P. (2015). Sharing a secret image with encapsulated shares in visual cryptography. Procedia Computer Science, 70, 462–468.Google Scholar
  8. 8.
    Begum, A. A. S., & Nirmala, S. (2018). Secure visual cryptography for medical image using modified cuckoo search. Multimedia Tools and Applications, 1–20.Google Scholar
  9. 9.
    Wadi, S. M., & Zainal, N. (2017). Enhanced hybrid image security algorithms for high definition images in multiple applications. Multidimensional Systems and Signal Processing, 1–24.Google Scholar
  10. 10.
    Kita, N., & Miyata, K. (2018). Magic sheets: Visual cryptography with common shares. Computational Visual Media, 4(2), 185–195.CrossRefGoogle Scholar
  11. 11.
    Do, Q., Martini, B., & Choo, K. K. R. (2018). The role of the adversary model in applied security research. Computers & Security.Google Scholar
  12. 12.
    Sreelaja, N. K., & Pai, G. V. (2012). Stream cipher for binary image encryption using Ant Colony Optimization based key generation. Applied Soft Computing, 12(9), 2879–2895.CrossRefGoogle Scholar
  13. 13.
    Aïssa, B., Nadir, D., & Mohamed, R. (2011, July). Image encryption using stream cipher algorithm with nonlinear filtering function. In 2011 International Conference on High Performance Computing and Simulation (HPCS) (pp. 830–835). IEEE.Google Scholar
  14. 14.
    El‐Shorbagy, M. A., Elhoseny, M., Hassanien, A. E., & Ahmed, S. H. (2018). A novel PSO algorithm for dynamic wireless sensor network multiobjective optimization problem. Transactions on Emerging Telecommunications Technologies, e3523.Google Scholar
  15. 15.
    Shankar, K., Lakshmanaprabu, S. K., Gupta, D., Khanna, A., & de Albuquerque, V. H. C. (2018). Adaptive optimal multi key based encryption for digital image security. Concurrency and Computation: Practice and Experience, e5122.Google Scholar
  16. 16.
    Li, Y., Xiong, C., Han, X., Du, H., & He, F. (2018). Internet-scale secret sharing algorithm with multimedia applications. Multimedia Tools and Applications, 1–6.Google Scholar
  17. 17.
    Liu, Y., & Chang, C. C. (2018). A turtle shell-based visual secret sharing scheme with reversibility and authentication. Multimedia Tools and Applications, 1–16.Google Scholar
  18. 18.
    Shankar, K., Elhoseny, M., Kumar, R. S., Lakshmanaprabu, S. K., & Yuan, X. (2018). Secret image sharing scheme with encrypted shadow images using optimal homomorphic encryption technique. Journal of Ambient Intelligence and Humanized Computing, 1–13.Google Scholar
  19. 19.
    Al-Khalid, R. I., Al-Dallah, R. A., Al-Anani, A. M., Barham, R. M., & Hajir, S. I. (2017). A secure visual cryptography scheme using private key with invariant share sizes. Journal of Software Engineering and Applications, 10(1), 1–10.CrossRefGoogle Scholar
  20. 20.
    Elhoseny, M., Farouk, A., Zhou, N., Wang, M.-M., Abdalla, S., & Batle, J. (2017). Dynamic multi-hop clustering in a wireless sensor network: Performance improvement. Wireless Personal Communications, Springer US, 95(4), 3733–3753.Google Scholar
  21. 21.
    Elhoseny, M., Tharwat, A., Yuan, X., & Hassanien, A. E. (2018). Optimizing K-coverage of mobile WSNs. Expert Systems with Applications, 92, 142–153.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of ComputingKalasalingam Academy of Research and EducationVirudhunagarIndia
  2. 2.Faculty of Computers and InformationMansoura UniversityMansouraEgypt

Personalised recommendations