A Novel Metaheuristic Based Visual Cryptography

Document Type : -

Authors

Babol Noshirvani University of Technology

Abstract

Visual cryptography is one of the newest techniques is image encryption. Visual cryptography encrypts visual information and generates two or more shares which contain no information separately, but reveal the secret when superposed. The main advantage of this scheme is that the decoding process does not need any knowledge of cryptography and human visual system is able to decrypt the secret message. In this article, a new encryption method based on particle swarm optimization is provided. The basis matrices are obtained using this approach and then used for encryption. In previous work, a Genetic Algorithm based method was proposed. In our work we fix a subtle yet crucial bug in the GA based method which is generating pictures with negative contrast in some cases and propose a simpler alternative. Simulation results show that the proposed method meets all the initial conditions of visual cryptography while decreasing the number of function evaluations and can provide a contrast enhancement. Moreover, the proposed method has the advantage of being generic and can be used in various threshold based visual cryptography.

Keywords


 [1]   Naor, M.; Shamir, A. “Visual Cryptography”; Workshop on the Theory and Application of Cryptographic Techniques, Springer, 1994.
[2]   Thomas, S. A.; Gharge, S. “Review on Various Visual Cryptography Schemes”; Int. Conf. Current Trends in Computer, Electrical, Electronics and Communication, Mysore, 2017, 1164-1167.
[3]   Jia, X.; Wang, D.; Nie, D.; Zhang, C. “Collaborative Visual Cryptography Schemes”; IEEE Trans. Circuits and Systems for Video Technology 2018, 28, 1056-1070.
[4]   Chiu, P. L.; Lee, K. H. “A Simulated Annealing Algorithm for General Threshold Visual Cryptography Schemes”;  IEEE Trans. Information Forensics and Security 2011, 6, 992 - 1001.
 [5]   Lee, K. H.; Chiu, P. L. “Image Size Invariant Visual Cryptography for General Access Structures Subject to Display Quality Constraints”; IEEE Trans. Image Proc. 2013, 22, 3830-41.
[6]   Buckley, N.;  Nagar, A.; Arumugam, S. “Evolution of Visual Cryptography Basis Matrices with Binary Chromosomes”;  IEEE 8th EUROSIM Congress on Modelling and Simulation 2013.
[7]   Arumugam, S.; Lakshmanan, R.; Nagar, A. K. “On (k, n)*-Visual Cryptography Scheme Designs”; Codes and Cryptography 2014, 71, 153-162.
[8]   Revenkar, P. S.;  Anjum, A.; Gandhare, W.  “Survey of Visual Cryptography Schemes”; Int. J. Security and Its Applications 2010, 4, 49-56.
[9]   Ramya, J.; Parvathavarthini, B. “An Extensive Review on Visual Cryptography Schemes”; IEEE Int. Conf. Control, Instrumentation, Communication and Computational Technologies, 2014.
[10] Hou, Y. C. “Visual Cryptography for Color Images”; Pattern Recognition 2003, 36, 1619-1629.
[11] Ateniese, G.; Blundo, C.;  De Santis, A.; Stinsonc, D. R. “Constructions and Bounds for Visual Cryptography”; Int. Colloquium on Automata, Languages, and Programming. 1996, 416-428.
[12] Hofmeister, T.;  Krause, M.; Simon, S. M. “Contrast-Optimal k Out of n Secret Sharing Schemes in Visual Cryptography”; Theoretical Computer Sci. 2000, 240, 471-485.
[13] Ateniese, G.; Blundo, C.;  De Santis, A.; Stinsonc, D. R. “Extended Capabilities for Visual Cryptography”; Theoretical Computer Sci. 2001, 250, 143-161.
[14] Mirghaderi, A.; Jolfaei, A. “A Novel Chaotic Image Encryption Scheme Using Chaotic Maps”; Adv. Defence Sci. Technol. 2011, 2, 111-124.
  • Receive Date: 23 April 2018
  • Revise Date: 16 September 2018
  • Accept Date: 21 November 2018
  • Publish Date: 23 September 2019