Low-Complexity Multiclass Encryption by Compressed Sensing

Valerio Cambareri, Mauro Mangia, Fabio Pareschi, Riccardo Rovatti, Gianluca Setti

Research output: Contribution to journalArticlepeer-review

134 Scopus citations

Abstract

The idea that compressed sensing may be used to encrypt information from unauthorized receivers has already been envisioned but never explored in depth since its security may seem compromised by the linearity of its encoding process. In this paper, we apply this simple encoding to define a general private-key encryption scheme in which a transmitter distributes the same encoded measurements to receivers of different classes, which are provided partially corrupted encoding matrices and are thus allowed to decode the acquired signal at provably different levels of recovery quality. The security properties of this scheme are thoroughly analyzed: first, the properties of our multiclass encryption are theoretically investigated by deriving performance bounds on the recovery quality attained by lower-class receivers with respect to high-class ones. Then, we perform a statistical analysis of the measurements to show that, although not perfectly secure, compressed sensing grants some level of security that comes at almost-zero cost and thus may benefit resource-limited applications. In addition to this, we report some exemplary applications of multiclass encryption by compressed sensing of speech signals, electrocardiographic tracks and images, in which quality degradation is quantified as the impossibility of some feature extraction algorithms to obtain sensitive information from suitably degraded signal recoveries.
Original languageEnglish (US)
Pages (from-to)2183-2195
Number of pages13
JournalIEEE Transactions on Signal Processing
Volume63
Issue number9
DOIs
StatePublished - May 26 2015
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-02-15

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Low-Complexity Multiclass Encryption by Compressed Sensing'. Together they form a unique fingerprint.

Cite this