DocumentCode :
432924
Title :
SINR, bit error rate, and Shannon capacity optimized spread-spectrum steganography
Author :
Gkizeli, Maria ; Pados, Dimitris A. ; Medley, Michael J.
Author_Institution :
Dept. of Electr. Eng., State Univ. of New York, Buffalo, NY, USA
Volume :
3
fYear :
2004
fDate :
24-27 Oct. 2004
Firstpage :
1561
Abstract :
For any given host image and (block) transform domain of interest, we derive the signature vector that when used for spread-spectrum (SS) message embedding that maximizes the signal-to-interference-plus-noise ratio (SINR) at the output of the maximum SINR linear filter receiver. Under a (colored) Gaussian assumption on the transform domain host data, we see that the same signature offers minimum probability of error message recovery at any host distortion level or -conversely- minimizes the host distortion for any probability of error target level. In addition, we show that the same signature maximizes the Shannon capacity of the covert link. All developments are then generalized to cover SS embedding in linearly processed block transform domain host data with orders of magnitude demonstrated improvement over current SS steganographic practices.
Keywords :
Gaussian processes; cryptography; data encapsulation; error statistics; optimisation; radio receivers; radiofrequency interference; spread spectrum communication; transforms; BER; Gaussian assumption; SINR; Shannon capacity; bit error rate; error probability; linear filter; message recovery; optimization; signal-to-interference-plus-noise ratio; spread-spectrum message embedding; spread-spectrum steganography; Bit error rate; Interference suppression; Nonlinear filters; Optimization methods; Pixel; Signal design; Signal to noise ratio; Spread spectrum communication; Steganography; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2004. ICIP '04. 2004 International Conference on
ISSN :
1522-4880
Print_ISBN :
0-7803-8554-3
Type :
conf
DOI :
10.1109/ICIP.2004.1421364
Filename :
1421364
Link To Document :
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