Privacy Preserving Scheme for Online Image Sharing


  • Yassir Southern Technical University, Shatra Technical Institute, Iraq


face detection, image encryption, photo sharing, privacy, chaotic cryptography


This paper presents a privacy protection solution for online photo share by obscuring faces in images, which keeps persons anonymous. The proposed system  contains two modules. The first is the face detection module to identify region of interest (ROI) which is faces. The second is a face encryption module, which encrypts the ROI pixels using keys so that the access to the faces is restricted. The face detection module uses skin color detector in YCbCr color space to detect skin areas in the image. Also, to overcome the illumination problems in color images, two color constancy methods were adopted for color correction and lighting of the input images. The edges of the image are utilized to separate the faces segments from the background or object that have similar skin color. Morphological operations such as erosion are applied to remove small areas and hole filling to remove any holes in the binary segments. In addition, the correct faces are located by using a set of features. The face encryption module uses two chaotic logistic maps. One map is used for shuffling the face area pixels and another map is used for encrypting the pixels. Both shuffling and encryption are done using a keys.  The face detection was tested on Caltech face database and showed a high detection rate and can localize face under different illumination conditions. The experiments on face encryption showed satisfactory results in various tests in terms of key space, PSNR, MSE and entropy analysis.


S. K. Rajput and A. Konidena, “PERFORMANCE ENHANCEMENT IN IMAGE ENCRYPTION USING AES,” Int. J. Innov. Adv. Comput. Sci., vol. 4, no. 1, pp. 16–19, 2015.

M.A.H.Al-Hamami,“AProposed Framework for Photos Copyright Protection in Facebook,” Int. J. Comput. Appl., vol. 162, no. 1, 2017.

K. Liang, J. K. Liu, R. Lu, and D. S. Wong, “Privacy concerns for photo sharing in online social networks,” IEEE Internet Comput., vol. 19, no. 2, pp. 58–63, 2014.

J. Chen, Z. Zhu, C. Fu, H. Yu, and L. Zhang, “An efficient image encryption scheme using gray code based permutation approach,” Opt. Lasers Eng., vol. 67, pp. 191–204, 2015.

C.-Y. Lin, C.-C. Chang, Y.-H. Chen, and P. Prangjarote, “Multimedia Privacy Protection System for Mobil Environments,” in 2011 Seventh International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2011, pp. 133–136.

L. A. Cutillo, R. Molva, and M. Önen, “Privacy preserving picture sharing: Enforcing usage control in distributed on-line social networks,” inProceedingsof theFifth Workshop on Social Network Systems,2012,p. 6.

L. Y. Deng, D. L. Lee, and Y. Liu, “Face Recognition Lock,” in 2013 International Conference on IT Convergence and Security (ICITCS), 2013, pp. 1–2.

O. A. Khashan, A. M. Zin, and E. A. Sundararajan, “Performance study of selective encryption in comparison to full encryption for still visual images,” J. Zhejiang Univ. Sci. C,vol.15, no. 6, pp. 435–444, 2014.

L. Zhang, T. Jung, C. Liu, X. Ding, X.-Y. Li, and Y. Liu, “Pop: Privacy-preserving outsourced photo sharing and searching for mobile devices,” in 2015 IEEE 35th International Conference on Distributed Computing Systems, 2015, pp. 308–317.

J. He et al., “Puppies: Transformation-supported personalized privacy preserving partial image sharing,” in 2016 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2016, pp. 359–370.

F. Li, J. Yu, L. Zhang, Z. Sun, and M. Lv, “A privacy-preserving method for photo sharing in instant message systems,” in Proceedings of the 2017 International Conference on Cryptography, Security and Privacy, 2017, pp. 38–43.

S. L. Phung, A. Bouzerdoum, and D. Chai, “Skin segmentation using color pixel classification: analysis and comparison,” IEEE Trans. Pattern Anal. Mach. Intell., no. 1, pp. 148–154, 2005.

N. Bigdeli, Y. Farid, and K. Afshar, “A robust hybrid method for image encryption based on Hopfield neural network,” Comput. Electr. Eng., vol. 38, no. 2, pp. 356–369, 2012.

J. D. D. Nkapkop, J. Y. Effa, J. Fouda, M. Alidou, L. Bitjoka, and M. Borda, “A fast image encryption algorithm based on chaotic maps and the linear diophantine equation,” Comput. Sci. Appl., vol. 1, no. 4, pp. 232–243, 2014.

K. H. Bin Ghazali, J. Ma, and R. Xiao, “An innovative face detection based on skin color segmentation,” Int. J. Comput. Appl., vol. 34, no. 2, pp. 6–10, 2011.

W.-C. Hu, C.-Y. Yang, D.-Y. Huang, and C.-H. Huang, “Feature-based face detection against skin-color like backgrounds with varying illumination,” J. Inf. Hiding Multimed. Signal Process., vol. 2, no. 2, pp. 123–132, 2011.

M. V Daithankar, K. J. Karande, and A. D. Harale, “Analysis of skin color models for face detection,” in 2014 International Conference on Communication and Signal Processing, 2014, pp. 533–537.

Q. Huynh-Thu, M. Meguro, and M. Kaneko, “Skin-color extraction in images with complex background and varying illumination,” in Sixth IEEE Workshop on Applications of Computer Vision, 2002.(WACV 2002). Proceedings., 2002, pp. 280–285.

Q. Liu and G. Peng, “A robust skin color based face detection algorithm,” in 2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010), 2010, vol. 2, pp.525–528.

F. Y. Shih, S. Cheng, C.-F. Chuang, and P. S. P. Wang, “Extracting faces and facial features from color images,” Int. J. Pattern Recognit. Artif. Intell., vol. 22, no. 03, pp. 515–534, 2008.

H.-J. Lin, S.-H. Yen, J.-P. Yeh, and M.-J. Lin, “Face detection based on skin color segmentation and SVM classification,” in 2008 Second International Conference on Secure System Integration and Reliability Improvement, 2008, pp. 230–231.

W. Zhang, B. Yu, G. J. Zelinsky, and D. Samaras, “Object class recognition using multiple layer boosting with heterogeneous features,” in 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), 2005, vol. 2, pp. 323–330.

Y. Ban, S.-K. Kim, S. Kim, K.-A. Toh, and S. Lee, “Face detection based on skin color likelihood,” Pattern Recognit., vol. 47, no. 4, pp. 1573–1585, 2014.

C. N. Khac, J. H. Park, and H.-Y. Jung, “Face detection using variance based Haar-like feature and SVM,” World Acad. Sci. Eng. Technol., vol. 60, pp. 165–168, 2009.