首页> 外文期刊>International Journal of Computer Trends and Technology >A Novel Mathematical Model for (t, n)-Threshold Visual Cryptography Scheme
【24h】

A Novel Mathematical Model for (t, n)-Threshold Visual Cryptography Scheme

机译:(t,n)-阈值视觉密码方案的新型数学模型

获取原文
           

摘要

As technology is progressing and more and more personal data is digitized, there is even more need for data security today than there has ever been. Protecting this critical data in a secure way against the unauthorised access is an immensely difficult and complicated research problem. Within the cryptographic community, many attempts have been in this regard. In visual cryptography, secret sharing offers a similar scheme, where a secret S, encoded into an image is shared among a group of n members, each of them holds a portion of the secret as their secret shares. The secret can only be retrieved when a certain number of t members (where t ≤ n) combine their shares together. And while any combination with fewer than t shares have no extra information about the secret than 0 shares. This kind of secret sharing system is known as (t, n) threshold scheme or toutofn VC scheme. In this paper, we discuss various types of visual cryptographic schemes emphasizing on improving the efficiency and capacity of the original schemes. An analysis on the optimal contrast of the recovered secret, the robustness and security issues of technique is also presented. This paper attempts to develop a mathematical model based on interpolation for visual cryptography. Such a model using Lagrange’s formula is implemented and experimental results are verified.
机译:随着技术的进步以及越来越多的个人数据被数字化,当今对数据安全性的需求比以往任何时候都更高。以安全的方式保护关键数据免受未经授权的访问是一个非常困难和复杂的研究问题。在密码界,在这方面已进行了许多尝试。在视觉密码学中,秘密共享提供了一种类似的方案,其中编码成图像的秘密S在一组n个成员之间共享,其中每个成员都将秘密的一部分作为其秘密共享。仅当一定数量的t个成员(其中t≤n)将其份额合并在一起时,才能检索此秘密。而且,尽管少于t股的任何组合都没有超过0股的秘密信息。这种秘密共享系统称为(t,n)阈值方案或toutofn VC方案。在本文中,我们讨论了各种类型的视觉密码方案,重点是提高原始方案的效率和容量。还提出了对所恢复秘密的最佳对比度,技术的鲁棒性和安全性问题的分析。本文尝试为可视密码学开发基于插值的数学模型。使用拉格朗日公式建立了这样的模型,并验证了实验结果。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号