Robust and secure image hashing
Abstract
Image hash functions find extensive applications in content authentication, database search, and watermarking. This paper develops a novel algorithm for generating an image hash based on Fourier transform features and controlled randomization. We formulate the robustness of image hashing as a hypothesis testing problem and evaluate the performance under various image processing operations. We show that the proposed hash function is resilient to content-preserving modifications, such as moderate geometric and filtering distortions. We introduce a general framework to study and evaluate the security of image hashing systems. Under this new framework, we model the hash values as random variables and quantify its uncertainty in terms of differential entropy. Using this security framework, we analyze the security of the proposed schemes and several existing representative methods for image hashing. We then examine the security versus robustness tradeoff and show that the proposed hashing methods can provide excellent security and robustness.
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The experiment measured the misjudgment rate < 10^-6 at t = 5, which meets practical application requirements.
“the experiment measured the misjudgment rate < 10 -6 at t = 5, which meets the practical application requirements [54].”
From Digital Image Copyright Protection and Management Approach—Based on Artificial Intelligence and Blockchain Technology (2025) · cites this paper as [54]
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- Authors
- Swaminathan, A., Mao, Y., & Wu, M.
- Affiliations
- Dept. of Electr. & Comput. Eng., Maryland Univ., USA
- Venue
- IEEE Transactions on Information Forensics and Security
- Published
- 2006-06
- Volume
- 1
- Issue
- 2
- Pages
- 215-230
- ISSN
- 1556-6013 (ISSN-L)
- 1556-6021
- OpenAlex
- W2109190643
- Cited by
- 552
- References
- 45
- Citations by year
- 2026: 11 · 2025: 14 · 2024: 12 · 2023: 17 · 2022: 21 · 2021: 22 · 2020: 33 · 2019: 26 · 2018: 26 · 2017: 30 · 2016: 38 · 2015: 37 · 2014: 33 · 2013: 43 · 2012: 42
- FWCI
- 31.11
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Information Forensics and Security (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Steganography and Watermarking Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Chaos-based Image/Signal Encryption
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Digital Media Forensic Detection
- Keywords
- image hashing, robustness, Fourier transform features, hypothesis testing, differential entropy, content authentication, geometric distortion
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