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...

Full description

Saved in:
Bibliographic Details
Published in2017 15th Annual Conference on Privacy, Security and Trust (PST) pp. 385 - 3852
Main Authors Ghaffaripour, Shadan, Younis, Fadi, Poon, Hoi Ting, Miri, Ali
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2017
Subjects
Compressed sensing
cryptanalysis
Encryption
Knowledge engineering
Neural networks
security
Sensors
signal processing
Online AccessGet full text

Cover

More Information
Summary: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.
DOI:10.1109/PST.2017.00052