基于人工神经网络的压缩感知安全性分析

Shadan Ghaffaripour, F. Younis, Hoi Ting Poon, A. Miri
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引用次数: 0

摘要

压缩感知(CS)技术在实际应用中得到了广泛的应用。最近,由于它们的特性,它们被提议用于加密算法。在本文中,我们提出了一个基于压缩感知的加密的经验安全性分析。使用神经网络模型,我们将展示这种类型的加密的安全性可能会受到损害。我们至少考虑了三种不同的攻击场景,在这些场景中,攻击可能会导致有关明文的部分信息在不知道CS密钥的情况下被泄露。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Analysis of the Security of Compressed Sensing Using an Artificial Neural Network
Compressed sensing (CS) schemes have been used in a wide number of applications in practice. Recently, they have been proposed for use in encryption algorithms because of their properties. In this paper, we present an empirical security analysis of compressed sensing-based encryption. Using a neural network model, we will show that the security of this type of encryption can be compromised. We consider at least three different scenarios in which an attack could occur causing partial information about the plaintext to be revealed without knowledge of the CS secret key.
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