Application of Artificial Neural Network in Cryptography

Bhavya Arora, K. Srishti, Nikita Khatri, V. Niranjan
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引用次数: 2

Abstract

In today's scenario where everything is just a click away, there is a huge concern for Intelligence Security. In this work, artificial neural network(ANN) has been explored to prevent any unaccredited access of data. Several kinds of cryptographic techniques are already in use to handle this problem. However, each of these techniques have their own advantages and limitations. Some techniques are more secure whereas some are less. In this work ANN is investigated in data security application by analyzing different types of semantic nets along with their architectures and compared. Further, scrutiny is done on the footing of their training algorithms by listing down their merits/demerits. A recurrent network is used to carry out the implementation of a finite state sequential machine which is used for cryptography purpose. Based on the analysis of obtained results, it is concluded that Artificial Neural Network can be effectively utilized as a contemporary technique to encrypt and decrypt a data.
人工神经网络在密码学中的应用
在如今一切都只需点击一下的情况下,人们对情报安全产生了巨大的担忧。在这项工作中,人工神经网络(ANN)已被探索以防止任何未经授权的数据访问。已经有几种加密技术被用来处理这个问题。然而,每种技术都有自己的优点和局限性。有些技术更安全,而有些则不安全。本文通过分析和比较不同类型的语义网络及其结构,研究了人工神经网络在数据安全方面的应用。此外,通过列出他们的优点/缺点,在他们的训练算法的基础上进行审查。本文采用循环网络实现了一种用于密码学目的的有限状态顺序机。通过对已有结果的分析,认为人工神经网络可以作为一种有效的当代数据加密和解密技术加以利用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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