Quantum Noise-based Adversarial Attack on Diffusion Models and Analysis of Defense Mechanisms

Sunjun Hwang

Quantum Noise-based Adversarial Attack on Diffusion Models and Analysis of Defense Mechanisms

Sunjun Hwang, Journal of Internet Computing and Services, Vol. 27, No. 1, pp. 201-212, Feb. 2026

10.7472/jksii.2026.27.1.201, Full Text:

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Keywords: Quantum Computing, Diffusion models, Adversarial attack, AI Security, Quantum Noise

Abstract

This study proposes a novel adversarial attack that injects quantum-inspired noise into diffusion models. Three representative noise channels—Amplitude Damping, Phase Damping, and Depolarizing—are analyzed using five standard benchmarks. Experiments show that quantum-inspired noise causes an average 11% greater performance degradation than classical noise and that conventional defenses fail to mitigate its effects. The findings reveal fundamental vulnerabilities of current diffusion models and suggest the necessity of quantum-aware defense strategies.

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Cite this article

[APA Style]

Hwang, S. (2026). Quantum Noise-based Adversarial Attack on Diffusion Models and Analysis of Defense Mechanisms. Journal of Internet Computing and Services, 27(1), 201-212. DOI: 10.7472/jksii.2026.27.1.201.

[IEEE Style]

S. Hwang, "Quantum Noise-based Adversarial Attack on Diffusion Models and Analysis of Defense Mechanisms," Journal of Internet Computing and Services, vol. 27, no. 1, pp. 201-212, 2026. DOI: 10.7472/jksii.2026.27.1.201.

[ACM Style]

Sunjun Hwang. 2026. Quantum Noise-based Adversarial Attack on Diffusion Models and Analysis of Defense Mechanisms. Journal of Internet Computing and Services, 27, 1, (2026), 201-212. DOI: 10.7472/jksii.2026.27.1.201.