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

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.

[1]  Andreas Uhl,et al.  SELECTIVE BITPLANE ENCRYPTION FOR SECURE TRANSMISSION OF IMAGE DATA IN MOBILE ENVIRONMENTS , 2002 .

[2]  Di Xiao,et al.  GLS coding based security solution to JPEG with the structure of aggregated compression and encryption , 2014, Commun. Nonlinear Sci. Numer. Simul..

[3]  Hongjun Liu,et al.  Color image encryption based on one-time keys and robust chaotic maps , 2010, Comput. Math. Appl..

[4]  Marc Van Droogenbroeck,et al.  Techniques for a selective encryption of uncompressed and compressed images , 2002 .

[5]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[6]  William Puech,et al.  Protection of Colour Images by Selective Encryption , 2013 .

[7]  Andreas Uhl,et al.  Confidential storage and transmission of medical image data , 2003, Comput. Biol. Medicine.

[8]  Osama M. Abu Zaid,et al.  Quality of Encryption Measurement of Bitmap Images with RC6, MRC6, and Rijndael Block Cipher Algorithms , 2007, Int. J. Netw. Secur..

[9]  Xingyuan Wang,et al.  Chaos-based partial encryption of SPIHT coded color images , 2013, Signal Process..

[10]  Thomas Stütz,et al.  Transparent Image Encryption Using Progressive JPEG , 2006, ISC.

[11]  S. R. Mahadeva Prasanna,et al.  A Partial Image Encryption Method with Pseudo Random Sequences , 2006, ICISS.

[12]  Chin-Chen Chang,et al.  A virtual image cryptosystem based upon vector quantization , 1998, IEEE Trans. Image Process..

[13]  Xi Chen,et al.  On the design of partial encryption scheme for multimedia content , 2013, Math. Comput. Model..

[14]  Balasubramanian Raman,et al.  Multimedia Encryption: A Brief Overview , 2009 .

[15]  Dan Zhang,et al.  Decryption of pure-position permutation algorithms , 2004, Journal of Zhejiang University. Science.

[16]  Malay Kishore Dutta,et al.  An Efficient Adaptive Encryption Algorithm for Digital Images , 2012, International Journal of Computer and Electrical Engineering.

[17]  Zyad Shaaban,et al.  Image Encryption Using DCT and Stream Cipher , 2009 .

[18]  Xiaobo Li,et al.  Partial encryption of compressed images and videos , 2000, IEEE Trans. Signal Process..

[19]  Abdullah Mohd Zin,et al.  An Efficient Adaptive of Transparent Spatial Digital Image Encryption , 2013 .

[20]  Rosalind Brackenbury A virtual image , 1971 .

[21]  Ljupco Kocarev,et al.  Theory and practice of chaotic cryptography , 2007 .

[22]  Rastislav Lukac,et al.  Efficient encryption of wavelet-based coded color images , 2005, Pattern Recognit..

[23]  Di Xiao,et al.  Edge-based lightweight image encryption using chaos-based reversible hidden transform and multiple-order discrete fractional cosine transform , 2013 .

[24]  A. A. El-Harby,et al.  Face Recognition: A Literature Review , 2008 .

[25]  Ritu Agarwal,et al.  Peformance analysis of data encryption algorithms , 2011, 2011 3rd International Conference on Electronics Computer Technology.

[26]  Rafat Parveen,et al.  Wavelet based partial image encryption , 2009, 2009 International Multimedia, Signal Processing and Communication Technologies.

[27]  Dinghui Zhang,et al.  Chaotic encryption and decryption of JPEG image , 2014 .

[28]  Kwok-Tung Lo,et al.  Optimal quantitative cryptanalysis of permutation-only multimedia ciphers against plaintext attacks , 2011, Signal Process..

[29]  Gaurav Bhatnagar,et al.  Selective image encryption based on pixels of interest and singular value decomposition , 2012, Digit. Signal Process..

[30]  J. S. Sohal,et al.  Performance Evaluation of Prewitt Edge Detector for Noisy Images , 2006 .

[31]  Yicong Zhou,et al.  A lossless encryption method for medical images using edge maps , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[32]  Nikolaos G. Bourbakis,et al.  A general quantitative cryptanalysis of permutation-only multimedia ciphers against plaintext attacks , 2008, Signal Process. Image Commun..

[33]  Di Xiao,et al.  Vulnerability to chosen-plaintext attack of a general optical encryption model with the architecture of scrambling-then-double random phase encoding. , 2013, Optics letters.

[34]  Mislav Grgic,et al.  Recent Advances in Multimedia Signal Processing and Communications , 2009 .