ArticlesNo Access

A NEURAL-NETWORK APPROACH FOR VISUAL CRYPTOGRAPHY AND AUTHORIZATION

TAI-WEN YUE

Computer Science and Engineering, Tatung University, Taiwan, ROC

Search for more papers by this author

and

SUCHEN CHIANG

Computer Science and Engineering, Tatung University, Taiwan, ROC

Search for more papers by this author

https://doi.org/10.1142/S012906570400198XCited by:5 (Source: Crossref)

Abstract

In this paper, we propose a neural-network approach for visual authorization, which is an application of visual cryptography (VC). The scheme contains a key-share and a set of user-shares. The administrator owns the key-share, and each user owns a user-share issued by the administrator from the user-share set. The shares in the user-share set are visually indistinguishable, i.e. they have the same pictorial meaning. However, the stacking of the key-share with different user-shares will reveal significantly different images. Therefore, the administrator (in fact, only the administrator) can visually recognize the authority assigned to a particular user by viewing the information appearing in the superposed image of key-share and user-share.

This approach is completely different from traditional VC approaches. The salient features include: (i) the access schemes are described using a set of graytone images, and (ii) the codebooks to fulfil them are not required; and (iii) the size of share images is the same as the size of target image.

Keywords:

References

G. Atenieseet al., Information and Computation 129(2), 86 (1996), DOI: 10.1006/inco.1996.0076. Crossref, Web of Science, Google Scholar
G. Atenieseet al., Theoretical Computer Science (1996). Google Scholar
C. Blundo, A. D. Santis and D. R. Stinson, J. Cryptology 12, 261 (1999), DOI: 10.1007/s001459900057. Crossref, Web of Science, Google Scholar
J. J. Hopfield, Proc. Nat. Acad. Sci. USA 79, 2554 (1982), DOI: 10.1073/pnas.79.8.2554. Crossref, Medline, Web of Science, Google Scholar
L. A. MacPherson, Grey level visual cryptography for general access structures, master thesis, Mathematics in Computer Science, Waterloo, Ontario, Canada (2002) . Google Scholar
M. Naor and B. Pinkas, Visual authentication and identification, CRYPTO (1997) pp. 322–336. Google Scholar
M. Naor and A. Shamir, Advances in Cryptology-Eurocrypt '94, Lecture Notes in Computer Science 950 (1995) pp. 1–12. Crossref, Google Scholar
N. Paul et al. , Authenticatin for remote voting , Workshop on Human-Computer Interaction and Security Systems ( 2003 ) . Google Scholar
T. M. Thompson, Visual cryptography, master's project, R.I.T. Department of Computer Science, Rochester Institute of Technology (2000) . Google Scholar
E. Verheul and H. V. Tilborg, Designs, Codes and Cryptography 11(2), 179 (1997), DOI: 10.1023/A:1008280705142. Crossref, Google Scholar
C. C. Wa, S. C. Tai and C. S. Yu, IEICE Trans. Fundamentals E83-A(8), 1589 (2000). Google Scholar
T. W. Yue, A goal-driven neural network approach for combinatorial optimization and invariant pattern recognition, Phd's thesis, Department of Computer Engineering, National Taiwan University, Taiwan (1992) . Google Scholar
T. W. Yue and Guo-Tai Chen, An auto-invertible neural network for image halftoning and restoration, Proc. IEEE Int. Conf. Neural Networks3 (1995) pp. 1450–1455. Google Scholar
T. W. Yue and S. C. Chiang, Quench, goalmatching and converge — The three-phase reasoning of a Q'tron neual network, Proc. IASTED Int. Conf. Artificial and Computational Intelligence (2002) pp. 54–59. Google Scholar
T. W. Yue and S. C. Chiang, The general neuralnetwork paradigm for visual cryptograph, IWANN 2001, LNCS 2048 (2001) pp. 196–206. Google Scholar
T. W. Yue and Z. Z. Lee, A goal-driven approach for combinatorial optimization using Q'tron neural networks, Proc. IASTED Int. Conf. Artificial and Computational Intelligence (2002) pp. 60–65. Google Scholar