Image authentication under geometric attacks via structure matching

Vishal Monga, Divyanshu Vats, Brian L. Evans

Research output: Chapter in Book/Report/Conference proceedingConference contribution

43 Citations (Scopus)

Abstract

Surviving geometric attacks in image authentication is considered to be of great importance. This is because of the vulnerability of classical watermarking and digital signature based schemes to geometric image manipulations, particularly local geometric attacks. In this paper, we present a general framework for image content authentication using salient feature points. We first develop an iterative feature detector based on an explicit modeling of the human visual system. Then, we compare features from two images by developing a generalized Hausdorff distance measure. The use of such a distance measure is crucial to the robustness of the scheme, and accounts for feature detector failure or occlusion, which previously proposed methods do not address. The proposed algorithm withstands standard benchmark (e.g. Stirmark) attacks including compression, common signal processing operations, global as well as local geometric transformations, and even hard to model distortions such as print and scan. Content changing (malicious) manipulations of image data are also accurately detected.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Multimedia and Expo, ICME 2005
Pages229-232
Number of pages4
DOIs
StatePublished - Dec 1 2005
EventIEEE International Conference on Multimedia and Expo, ICME 2005 - Amsterdam, Netherlands
Duration: Jul 6 2005Jul 8 2005

Publication series

NameIEEE International Conference on Multimedia and Expo, ICME 2005
Volume2005

Other

OtherIEEE International Conference on Multimedia and Expo, ICME 2005
CountryNetherlands
CityAmsterdam
Period7/6/057/8/05

Fingerprint

Authentication
Detectors
Electronic document identification systems
Watermarking
Signal processing

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Monga, V., Vats, D., & Evans, B. L. (2005). Image authentication under geometric attacks via structure matching. In IEEE International Conference on Multimedia and Expo, ICME 2005 (pp. 229-232). [1521402] (IEEE International Conference on Multimedia and Expo, ICME 2005; Vol. 2005). https://doi.org/10.1109/ICME.2005.1521402
Monga, Vishal ; Vats, Divyanshu ; Evans, Brian L. / Image authentication under geometric attacks via structure matching. IEEE International Conference on Multimedia and Expo, ICME 2005. 2005. pp. 229-232 (IEEE International Conference on Multimedia and Expo, ICME 2005).
@inproceedings{e5fa957cbbcf42cc9bf5f475264e32d3,
title = "Image authentication under geometric attacks via structure matching",
abstract = "Surviving geometric attacks in image authentication is considered to be of great importance. This is because of the vulnerability of classical watermarking and digital signature based schemes to geometric image manipulations, particularly local geometric attacks. In this paper, we present a general framework for image content authentication using salient feature points. We first develop an iterative feature detector based on an explicit modeling of the human visual system. Then, we compare features from two images by developing a generalized Hausdorff distance measure. The use of such a distance measure is crucial to the robustness of the scheme, and accounts for feature detector failure or occlusion, which previously proposed methods do not address. The proposed algorithm withstands standard benchmark (e.g. Stirmark) attacks including compression, common signal processing operations, global as well as local geometric transformations, and even hard to model distortions such as print and scan. Content changing (malicious) manipulations of image data are also accurately detected.",
author = "Vishal Monga and Divyanshu Vats and Evans, {Brian L.}",
year = "2005",
month = "12",
day = "1",
doi = "10.1109/ICME.2005.1521402",
language = "English (US)",
isbn = "0780393325",
series = "IEEE International Conference on Multimedia and Expo, ICME 2005",
pages = "229--232",
booktitle = "IEEE International Conference on Multimedia and Expo, ICME 2005",

}

Monga, V, Vats, D & Evans, BL 2005, Image authentication under geometric attacks via structure matching. in IEEE International Conference on Multimedia and Expo, ICME 2005., 1521402, IEEE International Conference on Multimedia and Expo, ICME 2005, vol. 2005, pp. 229-232, IEEE International Conference on Multimedia and Expo, ICME 2005, Amsterdam, Netherlands, 7/6/05. https://doi.org/10.1109/ICME.2005.1521402

Image authentication under geometric attacks via structure matching. / Monga, Vishal; Vats, Divyanshu; Evans, Brian L.

IEEE International Conference on Multimedia and Expo, ICME 2005. 2005. p. 229-232 1521402 (IEEE International Conference on Multimedia and Expo, ICME 2005; Vol. 2005).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Image authentication under geometric attacks via structure matching

AU - Monga, Vishal

AU - Vats, Divyanshu

AU - Evans, Brian L.

PY - 2005/12/1

Y1 - 2005/12/1

N2 - Surviving geometric attacks in image authentication is considered to be of great importance. This is because of the vulnerability of classical watermarking and digital signature based schemes to geometric image manipulations, particularly local geometric attacks. In this paper, we present a general framework for image content authentication using salient feature points. We first develop an iterative feature detector based on an explicit modeling of the human visual system. Then, we compare features from two images by developing a generalized Hausdorff distance measure. The use of such a distance measure is crucial to the robustness of the scheme, and accounts for feature detector failure or occlusion, which previously proposed methods do not address. The proposed algorithm withstands standard benchmark (e.g. Stirmark) attacks including compression, common signal processing operations, global as well as local geometric transformations, and even hard to model distortions such as print and scan. Content changing (malicious) manipulations of image data are also accurately detected.

AB - Surviving geometric attacks in image authentication is considered to be of great importance. This is because of the vulnerability of classical watermarking and digital signature based schemes to geometric image manipulations, particularly local geometric attacks. In this paper, we present a general framework for image content authentication using salient feature points. We first develop an iterative feature detector based on an explicit modeling of the human visual system. Then, we compare features from two images by developing a generalized Hausdorff distance measure. The use of such a distance measure is crucial to the robustness of the scheme, and accounts for feature detector failure or occlusion, which previously proposed methods do not address. The proposed algorithm withstands standard benchmark (e.g. Stirmark) attacks including compression, common signal processing operations, global as well as local geometric transformations, and even hard to model distortions such as print and scan. Content changing (malicious) manipulations of image data are also accurately detected.

UR - http://www.scopus.com/inward/record.url?scp=33747375321&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33747375321&partnerID=8YFLogxK

U2 - 10.1109/ICME.2005.1521402

DO - 10.1109/ICME.2005.1521402

M3 - Conference contribution

AN - SCOPUS:33747375321

SN - 0780393325

SN - 9780780393325

T3 - IEEE International Conference on Multimedia and Expo, ICME 2005

SP - 229

EP - 232

BT - IEEE International Conference on Multimedia and Expo, ICME 2005

ER -

Monga V, Vats D, Evans BL. Image authentication under geometric attacks via structure matching. In IEEE International Conference on Multimedia and Expo, ICME 2005. 2005. p. 229-232. 1521402. (IEEE International Conference on Multimedia and Expo, ICME 2005). https://doi.org/10.1109/ICME.2005.1521402