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CLC number: TP309

On-line Access: 2014-06-06

Received: 2013-09-18

Revision Accepted: 2014-01-22

Crosschecked: 2014-05-04

Cited: 6

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Journal of Zhejiang University SCIENCE C 2014 Vol.15 No.6 P.435-444


Performance study of selective encryption in comparison to full encryption for still visual images

Author(s):  Osama A. Khashan, Abdullah M. Zin, Elankovan A. Sundararajan

Affiliation(s):  Centre for Software Technology and Management, Faculty of Information Science and Technology, National University of Malaysia (UKM), Bangi 43600, Selangor, Malaysia

Corresponding email(s):   o_khashan@yahoo.com, amz@ftsm.ukm.my, elan@ftsm.ukm.my

Key Words:  Selective image encryption, Edge detection, Face detection

Osama A. Khashan, Abdullah M. Zin, Elankovan A. Sundararajan. Performance study of selective encryption in comparison to full encryption for still visual images[J]. Journal of Zhejiang University Science C, 2014, 15(6): 435-444.

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A1 - Osama A. Khashan
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DOI - 10.1631/jzus.C1300262

Securing digital images is becoming an important concern in today’s information security due to the extensive use of secure images that are either transmitted over a network or stored on disks. Image encryption is the most effective way to fulfil confidentiality and protect the privacy of images. Nevertheless, owing to the large size and complex structure of digital images, the computational overhead and processing time needed to carry out full image encryption prove to be limiting factors that inhibit it of being used more heavily in real time. To solve this problem, many recent studies use the selective encryption approach to encrypt significant parts of images with a hope to reduce the encryption overhead. However, it is necessary to realistically evaluate its performance compared to full encryption. In this paper, we study the performance and efficiency of image segmentation methods used in the selective encryption approach, such as edges and face detection methods, in determining the most important parts of visual images. Experiments were performed to analyse the computational results obtained by selective image encryption compared to full image encryption using symmetric encryption algorithms. Experiment results have proven that the selective encryption approach based on edge and face detection can significantly reduce the time of encrypting still visual images as compared to full encryption. Thus, this approach can be considered a good alternative in the implementation of real-time applications that require adequate security levels.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


[1]Amigó, J.M., Kocarev, L., Szczepanski, J., 2007. Theory and practice of chaotic cryptography. Phys. Lett. A, 366(3):211-216.

[2]Bhatnagar, G., Wu, Q.M., 2012. Selective image encryption based on pixels of interest and singular value decomposition. Dig. Signal Process., 22:648-663.

[3]Chen, T.S., Chang, C.C., Hwang, M.S., 1998. A virtual image cryptosystem based upon vector quantization. IEEE Trans. Image Process., 7(10):1485-1488.

[4]Cheng, H., Li, X., 2000. Partial encryption of compressed images and videos. IEEE Trans. Signal Process., 48(8):2439-2451.

[5]Droogenbroeck, M.V., Benedett, R., 2002. Techniques for a selective encryption of uncompressed and compressed images. Proc. Advanced Concepts for Intelligent Vision Systems, p.90-97.

[6]El-Fishawy, N., Abu Zaid, O.M., 2007. Quality of encryption measurement of bitmap images with RC6, MRC6, and Rijndael block cipher algorithms. Int. J. Network Secur., 5(3):241-251.

[7]Flayh, N.A., Parveen, R., Ahson, S.I., 2009. Wavelet based partial image encryption. Proc. Int. Multimedia, Signal Processing and Communication Technologies, p.32-35.

[8]Khashan, O.A., Zin, A.M., 2013. An efficient adaptive of transparent spatial digital image encryption. Proc. 4th Int. Conf. on Electrical Engineering and Informatics, p.288-297.

[9]Krikor, L., Baba, S., Arif, T., et al., 2009. Image encryption using DCT and stream cipher. Eur. J. Sci. Res., 32(1):48-58.

[10]Kulkarni , N.S., Raman, B., Gupta, I., 2009. Multimedia encryption: a brief overview. Recent Advances in Multimedia Signal Processing and Communications Studies in Computational Intelligence. In: Grgic, M., Delac, K., Ghanbari, M. (Eds.), Studies in Computational Intelligence, Springer Heidelberg, 231:417-449.

[11]Li, C., Lo, K., 2011. Optimal quantitative cryptanalysis of permutation-only multimedia ciphers against plaintext attacks. Signal Process., 91(4):949-954.

[12]Li, S., Li, C., Chen, G., et al., 2008. A general quantitative cryptanalysis of permutation-only multimedia ciphers against plaintext attacks. Signal Process. Image Commun., 23(3):212-223.

[13]Lian, S., Chen, X., 2013. On the design of partial encryption scheme for multimedia content. Math. Comput. Model., 57(11-12):2613-2624.

[14]Liu, H.J., Wang, X.Y., 2010. Color image encryption based on one-time keys and robust chaotic maps. Comput. Math. Appl., 59(10):3320-3327.

[15]Maini, R., Sohal, J.S., 2006. Performance evaluation of Prewitt edge detector for noisy images. Int. J. Graph. Vis. Image Process., 6(3):39-46.

[16]Martin, K., Lukac, R., Plataniotis, K., 2005. Efficient encryption of wavelet-based coded color images. Pattern Recogn., 38(7):1111-1115.

[17]Norcen, R., Podesser, M., Pommer, A., et al., 2003. Confidential storage and transmission of medical image data. Comput. Biol. Med., 33(3):277-292.

[18]OpenCV, 2013. Open Source Computer Vision Library. Available from http://opencv.org/.

[19]Podesser, M., Schmidt, H.P., Uhl, A., 2002. Selective bitplane encryption for secure transmission of image data in mobile environments. Proc. 5th Nordic Signal Processing Symp., p.1034-1037.

[20]Prewitt, J.M.S., 1970. Object Enhancement and Extraction: Picture Processing and Psychopictorics. Academic Press Inc., USA, p.75-150.

[21]Puech, W., Bors, A.G., Rodrigues, J.M., 2013. Protection of colour images by selective encryption. Adv. Color Image Process. Anal., p.397-421.

[22]Shekhar, S., Srivastava, H., Dutta, M.K., 2012. An efficient adaptive encryption algorithm for digital images. Int. J. Comput. Electr. Eng., 4(3):380-383.

[23]Stutz, T., Uhl, A., 2006. Transparent image encryption using progressive JPEG. LNCS, 4176:286-298.

[24]Subba Rao, Y.V., Mitra, A., Mahadeva Prasanna, S.R., 2006. A partial image encryption method with pseudo random sequences. LNCS, 4332:315-325.

[25]Tolba, A.S., El-Baz, A.H., El-Harby, A.A., 2006. Face recognition: a literature review. Int. J. Signal Process., 2(2):88-103.

[26]Verma, O.P., Agarwal, R., Dafouti, D., et al., 2011. Performance analysis of data encryption algorithms. 3rd IEEE Int. Conf. on Electronics Computer Technology, p.399-403.

[27]Viola, P., Jones, M., 2001. Rapid object detection using a boosted cascade of simple features. IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, p.511-518.

[28]Zhang, D., Zhang, F., 2013. Chaotic encryption and decryption of JPEG image. Optik-Int. J. Light Electron Opt., 125(2):717-720.

[29]Zhang, X., Wang, X., 2013. Chaos-based partial encryption of SPIHT coded color images. Signal Process., 93(9):2422-2431.

[30]Zhang, Y., Xiao, D., Wen, W., et al., 2013a. Vulnerability to chosen-plaintext attack of a general optical encryption model with the architecture of scrambling-then-double random phase encoding. Opt. Lett., 38(21):4506-4509.

[31]Zhang, Y., Xiao, D., Wen, W., et al., 2013b. Edge-based lightweight image encryption using chaos-based reversible hidden transform and multiple-order discrete fractional cosine transform. Opt. Laser Technol., 54:1-6.

[32]Zhang, Y., Xiao, D., Liu, H., et al., 2013c. GLS coding based security solution to JPEG with the structure of aggregated compression and encryption. Commun. Nonl. Sci. Numer. Simul., 19(5):1366-1374.

[33]Zhao, X.Y., Chen, G., Zhang, D., et al., 2004. Decryption of pure-position permutation algorithms. J. Zhejiang Univ. Sci., 5(7):803-809.

[34]Zhou, Y., Panetta, K., Agaian, S., 2009. A lossless encryption method for medical images using edge maps. 31st Annual Int. Conf. on IEEE Engineering in Medicine & Biology Society, p.3707-3710.

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