Secure spread spectrum watermarking for multimedia
Abstract
This paper presents a secure (tamper-resistant) algorithm for watermarking images, and a methodology for digital watermarking that may be generalized to audio, video, and multimedia data. We advocate that a watermark should be constructed as an independent and identically distributed (i.i.d.) Gaussian random vector that is imperceptibly inserted in a spread-spectrum-like fashion into the perceptually most significant spectral components of the data. We argue that insertion of a watermark under this regime makes the watermark robust to signal processing operations (such as lossy compression, filtering, digital-analog and analog-digital conversion, requantization, etc.), and common geometric transformations (such as cropping, scaling, translation, and rotation) provided that the original image is available and that it can be successfully registered against the transformed watermarked image. In these cases, the watermark detector unambiguously identifies the owner. Further, the use of Gaussian noise, ensures strong resilience to multiple-document, or collusional, attacks. Experimental results are provided to support these claims, along with an exposition of pending open problems.
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Audio watermarking: features, applications and algorithms
Arnold, M. (2000) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme.2000.871531 · Cited by 227 · see citing works
Watermarking and authentication of quantum images based on restricted geometric transformations
Iliyasu, A. M., Le, P. Q., Dong, F., & Hirota, K. (2011) · Information Sciences · doi:10.1016/j.ins.2011.09.028 · Cited by 223 · see citing works
An Oblivious Watermarking for 3-D Polygonal Meshes Using Distribution of Vertex Norms
Cho, J.-W., Prost, R., & Jung, H.-Y. (2006) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2006.882111 · Cited by 226 · see citing works
Some general methods for tampering with watermarks
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Self-citationCollusion-resistant fingerprinting for multimedia
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Watermaking three-dimensional polygonal models
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Reversible Image Steganography Scheme Based on a U-Net Structure
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Audio Signal Processing and Coding
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A survey of watermarking techniques applied to multimedia
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Advances in Digital Video Content Protection
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Data hiding in image and video .I. Fundamental issues and solutions
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Asymptotically optimal detection for additive watermarking in the DCT and DWT domains
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Cocktail watermarking for digital image protection
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The use of watermarks in the protection of digital multimedia products
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Toward Robust Logo Watermarking Using Multiresolution Image Fusion Principles
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- Authors
- Cox, I. J., Kilian, J., Leighton, F. T., & Shamoon, T.
- Affiliations
- NEC (Japan) (JP)
- Massachusetts Institute of Technology (US)
- ORCID
- Cox, I.J.
- Venue
- IEEE Transactions on Image Processing
- Published
- 1997-12
- Volume
- 6
- Issue
- 12
- Pages
- 1673-1687
- ISSN
- 1057-7149 (ISSN-L)
- 1941-0042
- OpenAlex
- W2116467012
- Semantic Scholar
- a5eaa0b77d774745409499be2a2f16c506156161
- Cited by
- 5,299
- References
- 70
- Citations by year
- 2026: 65 · 2025: 60 · 2024: 48 · 2023: 69 · 2022: 74 · 2021: 85 · 2020: 84 · 2019: 112 · 2018: 132 · 2017: 160 · 2016: 168 · 2015: 201 · 2014: 211 · 2013: 240 · 2012: 289
- FWCI
- 98.40
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Image Processing (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Steganography and Watermarking Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Digital Media Forensic Detection
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Data Compression Techniques
- Keywords
- digital watermarking, spread spectrum watermarking, tamper resistance, Gaussian random vectors, image watermarking, watermark robustness, lossy compression, geometric transformations, image registration
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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