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Image Encryption and Cluster Based Framework for Secured Image Transmission in Wireless Sensor Networks

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Abstract

Wireless Sensors are used in many real life applications including traffic monitoring to capture the video, converting the video into frames of images and to transmit them to the sink node for analysis. In such a scenario, security is an important issue to be tackled in wireless image transmission due to the presence of attackers in the wireless channel. Here, most of the attackers try to read the information transferred in the network passively in order to misuse the information for personal gains. In order to provide a solution to this problem, a new Elliptic Curve based key selection and Hill Cipher based encryption scheme is proposed in which the keys are permuted to enhance the size of the key to suite the size of the image matrix leading to a secured transmission by effective encryption of the images that are transmitted through wireless sensor networks. Finally, a secured transmission framework using clusters is proposed to make the proposed secure routing algorithm called Elliptic curve Hill cipher and Cluster based Encrypted Routing Algorithm to be more effective with respective increase in security reduction in delay and increase in packet delivery ratio. The proposed algorithm and the architectural framework developed in this work has been tested through experiments and proved that the proposed secure routing algorithm is more efficient when it is used in wireless applications that suite the framework proposed in this work.

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References

  1. Kim, J., Jang, K. Y., Choo, H., & Kim, W. (2007). Energy efficient LEACH with TCP for wireless sensor networks. In Computational science and its applicationsICCSA 2007 (pp. 275–285).

  2. Younis, O., & Fahmy, S. (2004). HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Transactions on Mobile Computing,3(4), 366–379.

    Article  Google Scholar 

  3. Younis, O., & Fahmy, S. (2004). Distributed clustering in ad-hoc sensor networks: A hybrid, energy-efficient approach. In Proceedings of IEEE INFOCOM, March 2004, an extended version appears in IEEE transactions on mobile computing (Vol. 3(4)), October–December, 2004.

  4. Cheng, H., & Li, X. (2000). Partial encryption of compressed images and videos. IEEE Transactions on Signal Processing,48(8), 2439–2451.

    Article  Google Scholar 

  5. Mukesh, R., Damodaram, A., & Subbiah Bharathi, V. (2008). Robust and secure image transmission in wireless sensor networks using enhanced compression and encryption. In ACST’08 proceedings of the 4th IASTED international conference on advances in computer science and technology (pp. 174–178).

  6. Wenjun, L., Varna, A. L., & Min, W. (2014). Confidentiality-preserving image search: A comparative study between homomorphic encryption and distance-preserving randomization. IEEE Access,2, 125–141.

    Article  Google Scholar 

  7. Gonçalves, D. O., & Costa, D. G. (2015). A survey of image security in wireless sensor networks. Journal of Imaging,1, 4–30.

    Article  Google Scholar 

  8. Taleb, A. A., & Tareq, A. (2014). Depth first based sink mobility model for wireless sensor networks. International Journal of Electrical and Electronics Computer Systems,19, 9–14.

    Google Scholar 

  9. Van, N. N. (2017). An enhanced random waypoint mobility model. International Journal of Computer Networks and Communication Security,5, 148–152.

    Google Scholar 

  10. Tabatabaei, S. A. H., Ur-Rehman, O., Zivic, N., & Ruland, C. (2015). Secure and robust two-phase image authentication. IEEE Transactions on Multimedia,17(7), 945–956.

    Article  Google Scholar 

  11. Elhoseny, M., Elminir, H., Riad, A., & Yuan, X. (2016). A secure data routing schema for WSN using elliptic curve cryptography and homomorphic encryption. Journal of King Saud University Sciences—Computer and Information,28, 262–275.

    Article  Google Scholar 

  12. Elhoseny, M., Elminir, H., Riad, A., & Yuan, X. (2016). A secure data routing schema for WSN using elliptic curve cryptography and homomorphic encryption. Journal of King Saud University—Computer and Information Sciences,28, 262–275.

    Article  Google Scholar 

  13. Elhoseny, M., Elhoseny, M., Farouk, A., Farouk, A., Batle, J., Shehab, A., et al. (2017). Secure image processing and transmission schema in cluster-based wireless sensor network secure image processing and transmission schema in cluster-based wireless sensor network (2 Vols., Edition: 1022-1040, Chapter: 45). In A. E. Hassanien & T. Gaber (Eds.), Handbook of research on machine learning innovations and trends. Pennsylvania: IGI Global. https://doi.org/10.4018/978-1-5225-2229-4.ch045.

    Chapter  Google Scholar 

  14. Stallings, W. (2013). Cryptography and network security: Principles and practice. London: Pearson Education.

    Google Scholar 

  15. Cui, H., Yuan, X., & Wang, C. (2017). Harnessing encrypted data in cloud for secure and efficient mobile image sharing. IEEE Transactions on Mobile Computing,16(5), 1315–1329.

    Article  Google Scholar 

  16. Hou, J., Xi, R., Liu, P., & Liu, T. (2017). The switching fractional order chaotic system and its application to image encryption. IEEE/CAA Journal of Automatica Sinica,4(2), 381–388.

    Article  MathSciNet  Google Scholar 

  17. Muthurajkumar, S., Ganapathy, S., Vijayalakshmi, M., & Kannan, A. (2017). An intelligent secured and energy efficient routing algorithm for MANETs. Wireless Personal Communications,96(2), 1753–1769.

    Article  Google Scholar 

  18. Logambigai, R., Ganapathy, S., & Kannan, A. (2018). Energy-efficient grid-based routing algorithm using intelligent fuzzy rules for wireless sensor networks. Computers & Electrical Engineering,68, 62–75.

    Article  Google Scholar 

  19. Elhoseny, M., Ramirez-Gonzalez, G., Abu-Elnasr, O. M., Shawkat, S. A., Arunkumar, N., & Farouk, A. (2018). Secure medical data transmission model for IoT-based healthcare systems. IEEE Access,6, 20596–20608.

    Article  Google Scholar 

  20. Zhang, X., & Wang, X. (2018). Digital image encryption algorithm based on elliptic curve public cryptosystem. IEEE Access,6, 70025–70034.

    Article  Google Scholar 

  21. Abdel-latif, A. A., Abd-el-atty, B., & Talha, M. (2018). Robust encryption of quantum medical images. IEEE Access,6, 1073–1081.

    Article  Google Scholar 

  22. Dutta, A., Naveen Kumar, K., Sai, N., & Chintala, R. R. (2018). An efficient light weight cryptography algorithm scheme for WSN devices using chaotic map and GE. International Journal of Pure and Applied Mathematics,118(20), 861–875.

    Google Scholar 

  23. He, J., Huang, S., Tang, S., & Huang, J. (2018). JPEG image encryption with improved format compatibility and file size preservation. IEEE Transactions on Multimedia,20(10), 2645–2658.

    Article  Google Scholar 

  24. Boussif, M., Aloui, N., & Cherif, A. (2018). Secured cloud computing for medical data based on watermarking and encryption. IET Networks,7(5), 294–298.

    Article  Google Scholar 

  25. Elumalaivasan, P., Kulothungan, K., Ganapathy, S., & Kannan, A. (2016). Trust based ciphertext policy attribute based encryption techniques for decentralized disruption tolerant networks. Australian Journal of Basic and Applied Sciences,10(2), 18–26.

    Google Scholar 

  26. Sangeetha, G., Vijayalakshmi, M., Ganapathy, S., & Kannan, A. (2019). An improved congestion-aware routing mechanism in sensor networks using fuzzy rule sets. Peer-to-Peer Networking and Applications. https://doi.org/10.1007/s12083-019-00821-4.

    Article  Google Scholar 

  27. Rajeswari, A. R., Kulothungan, K., Ganapathy, S., & Kannan, A. (2019). A trusted fuzzy based stable and secure routing algorithm for effective communication in mobile ad-hoc networks. Peer-to-Peer Networking and Applications,12, 1076–1096.

    Article  Google Scholar 

  28. Thangaramya, K., Kulothungan, K., Logambigai, R., Selvi, M., Ganapathy, S., & Kannan, A. (2019). Energy aware cluster and neuro-fuzzy based routing algorithm for wireless sensor networks in IoT. Computer Networks,151, 211–223.

    Article  Google Scholar 

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Correspondence to Jayanthi Ramasamy.

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Ramasamy, J., Kumaresan, J.S. Image Encryption and Cluster Based Framework for Secured Image Transmission in Wireless Sensor Networks. Wireless Pers Commun 112, 1355–1368 (2020). https://doi.org/10.1007/s11277-020-07106-7

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