New secure partial encryption method for medical images using graph coloring problem

The traffic of digital images has been quickly increased in the network. Security of image processing became important for many sectors, namely for medical applications. Currently, the transmission of medical images is a daily routine. The large volume of data exchange has motivated the development of new methods to reduce the cost. Partial encryption is an approach to reduce the computational resources for huge volumes of multimedia. This paper introduces a new and secure approach, called graph coloring problem cryptography, to encrypt partially the medical images using the graph coloring problem (GCP). Before encrypting the medical images using advanced encryption standard algorithm, we use a GCP algorithm to localize and select some optimal positions of the pixels in the original images. Thus, the key of the cryptographic method is hard to be detected and extracted by the hackers. We get an acceptable percentage of the encrypted data for better security with a lower cost compared with the total image encryption.

[1]  Douglas W. Jones,et al.  Application of splay trees to data compression , 1988, CACM.

[2]  Marc Van Droogenbroeck.  Partial encryption of images for real-time applications , 2004 .

[3]  Pascal Brisset,et al.  Graph Coloring for Air Traffic Flow Management , 2004, Ann. Oper. Res..

[4]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[5]  El Mamoun Souidi,et al.  A New Steganographic Method For Grayscale Image Using Graph Coloring Problem , 2013 .

[6]  William Puech,et al.  A Selective Encryption for Heterogenous Color JPEG Images Based on VLC and AES Stream Cipher , 2006, CGIV.

[7]  Michel Gamache,et al.  A graph coloring model for a feasibility problem in monthly crew scheduling with preferential bidding , 2007, Comput. Oper. Res..

[8]  Tenkasi V. Ramabadran,et al.  Near-lossless compression of medical images through entropy-coded DPCM , 1994, IEEE Trans. Medical Imaging.

[9]  A. Gamst,et al.  Some lower bounds for a class of frequency assignment problems , 1986, IEEE Transactions on Vehicular Technology.

[10]  Nikolaos G. Bourbakis,et al.  Picture data encryption using scan patterns , 1992, Pattern Recognit..

[11]  Vincent Rijmen,et al.  The Design of Rijndael , 2002, Information Security and Cryptography.

[12]  William Puech,et al.  Crypto-compression of medical images by selective encryption of DCT , 2005, 2005 13th European Signal Processing Conference.

[13]  D. de Werra,et al.  An introduction to timetabling , 1985 .

[14]  Frank Thomson Leighton,et al.  A Graph Coloring Algorithm for Large Scheduling Problems. , 1979, Journal of research of the National Bureau of Standards.

[15]  Ghassan Al-Regib,et al.  Improved selective encryption techniques for secure transmission of MPEG video bit-streams , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[16]  Yossi Matias,et al.  A Video Scrambling Technique Based On Space Filling Curves , 1987, CRYPTO.

[17]  Tracy Bradley Maples,et al.  Performance Study of a Selective Encryption Scheme for the Security of Networked, Real-Time Video , 1995, Proceedings of Fourth International Conference on Computer Communications and Networks - IC3N'95.

[18]  Andrew Lim,et al.  Robust Graph Coloring for Uncertain Supply Chain Management , 2005, Proceedings of the 38th Annual Hawaii International Conference on System Sciences.

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

[20]  Daniel Brélaz,et al.  New methods to color the vertices of a graph , 1979, CACM.

[21]  Amir Said.  Measuring the strength of partial encryption schemes , 2005, IEEE International Conference on Image Processing 2005.

[22]  Alain Hertz,et al.  Using tabu search techniques for graph coloring , 1987, Computing.