This paper investigates the weaknesses of image watermarking techniques. We present WAVES (Watermark Analysis Via Enhanced Stress-testing), a novel benchmark for assessing watermark robustness, overcoming the limitations of current evaluation methods.WAVES integrates detection and identification tasks, and establishes a standardized evaluation protocol comprised of a diverse range of stress tests. The attacks in WAVES range from traditional image distortions to advanced and novel variations of adversarial, diffusive, and embedding-based attacks. We introduce a normalized score of attack potency which incorporates several widely used image quality metrics and allows us to produce of an ordered ranking of attacks. Our comprehensive evaluation over reveals previously undetected vulnerabilities of several modern watermarking algorithms. WAVES is envisioned as a toolkit for the future development of robust watermarking systems.
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Laser spectroscopic technique for direct identification of a single virus I: FASTER CARS
From the famous 1918 H1N1 influenza to the present COVID-19 pandemic, the need for improved viral detection techniques is all too apparent. The aim of the present paper is to show that identification of individual virus particles in clinical sample materials quickly and reliably is near at hand. First of all, our team has developed techniques for identification of virions based on a modular atomic force microscopy (AFM). Furthermore, femtosecond adaptive spectroscopic techniques with enhanced resolution via coherent anti-Stokes Raman scattering (FASTER CARS) using tip-enhanced techniques markedly improves the sensitivity [M. O. Scully, et al ., Proc. Natl. Acad. Sci. U.S.A. 99, 10994–11001 (2002)].
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- Award ID(s):
- 2013771
- PAR ID:
- 10284753
- Date Published:
- Journal Name:
- Proceedings of the National Academy of Sciences
- Volume:
- 117
- Issue:
- 45
- ISSN:
- 0027-8424
- Page Range / eLocation ID:
- 27820 to 27824
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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