Logo image
Back
FORENSIC IDENTIFICATION OF COMPRESSIVELY SENSED SIGNALS
Conference proceeding   Open access

FORENSIC IDENTIFICATION OF COMPRESSIVELY SENSED SIGNALS

Xiaoyu Chu, Matthew C. Stamm, K. J. Ray Liu and IEEE
2012 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP 2012), pp 257-260
01 Jan 2012
DOI: https://doi.org/10.1109/ICIP.2012.6466844
url
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.467.1074View
SubmittedOpen Access (License Unspecified),  Open

Abstract

Imaging Science & Photographic Technology Science & Technology Technology
Identifying a signal's origin and how it was acquired is an important problem for digital forensics. Recently, compressive sensing has achieved substantial attention due to its ability to accurately acquire sparse signals at rates below the Nyquist rate. The increased popularity of this signal acquisition technique gives rise to a new forensic problem: is it possible to distinguish signals that have been compressively sensed from traditionally sampled ones? In our previous work, we addressed this problem of differentiating between traditionally acquired and compressively sensed images. In this paper, we examine the problem of distinguishing traditionally sampled signals from compressively sensed ones for a broader class of signals. We categorize those compressive sensing applicable signals into two cases: sparse signals with noise and nearly sparse signals. For each category, we discuss the traces left in a signal by compressive sensing and propose a corresponding detection scheme. Experimental results show that both of our proposed detection schemes can be effectively used to distinguish compressively sensed signals from traditionally sensed signals.

Metrics

12 Record Views
1 citations in Web of Science
2 citations in Scopus

Details

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Web of Science research areas
Imaging Science & Photographic Technology
Logo image