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Bi-level protected compressive sampling

Version 2 2024-06-04, 14:25
Version 1 2018-02-12, 15:41
journal contribution
posted on 2024-06-04, 14:25 authored by Leo ZhangLeo Zhang, KW Wong, Y Zhang, J Zhou
Some pioneering works have investigated embedding cryptographic properties in compressive sampling (CS) in a way similar to one-time pad symmetric cipher. This paper tackles the problem of constructing a CS-based symmetric cipher under the key reuse circumstance, i.e., the cipher is resistant to common attacks even when a fixed measurement matrix is used multiple times. To this end, we suggest a bi-level protected CS (BLP-CS) model which makes use of the advantage of measurement matrix construction without restricted isometry property (RIP). Specifically, two kinds of artificial basis mismatch techniques are investigated to construct key-related sparsifying bases. It is demonstrated that the encoding process of BLP-CS is simply a random linear projection, which is the same as the basic CS model. However, decoding the linear measurements requires knowledge of both the key-dependent sensing matrix and its sparsifying basis. The proposed model is exemplified by sampling images as a joint data acquisition and protection layer for resource-limited wireless sensors. Simulation results and numerical analyses have justified that the new model can be applied in circumstances where the measurement matrix can be reused.

History

Journal

IEEE transactions on multimedia

Volume

18

Pagination

1720-1732

Location

Piscataway, N.J.

ISSN

1520-9210

Language

eng

Publication classification

C Journal article, C1.1 Refereed article in a scholarly journal

Copyright notice

2016, IEEE

Issue

9

Publisher

Institute of Electrical and Electronics Engineers