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Home/Authors/Zongmin Zhang

Zongmin Zhang

3 indexed papers

Recent (6 mo)
3
With code
0
Influential cites
0
Benchmarked
0

Publications per year

3
26

Top categories

Crypto×3Sound×2AI×1Audio and Speech Processing×1Vision×1

Frequent co-authors

Yifan Liao3×
Zhen Sun3×
Xinhu Zheng3×
Xinlei He3×
Yule Liu2×
Jiaheng Wei2×

Research Timeline

2026
Stego Battlefield: Evaluating Image Steganography Attacks and Steganalysis Defenses

The paper introduces SADBench, a systematic benchmark designed to evaluate both the effectiveness of steganographic attacks injecting harmful content and the robustness of steganalysis defenses against these threats.

Escaping the Linearity Trap: Manifold Detours for Black-Box Adversarial Attacks on Singing Audio Deepfake Detection

The paper introduces MARS, a novel meta-adversarial framework that significantly improves black-box adversarial attacks against state-of-the-art Singing Voice Deepfake Detection (SVDD) systems by escaping the Linearity Trap.

Beyond Waveform Robustness: Robust Feature-Vocoder Adversarial Attacks on Automatic Speech Recognition

The paper introduces a novel Clean-Referenced Feature-Vocoder Attack, a black-box adversarial attack that perturbs high-level SSL feature representations instead of raw audio waveforms, achieving superior transferability and robustness against modern ASR defenses.

Highlighted terms show continued research focus across papers

Papers

cs.SDcs.AIcs.CRRecentJun 4, 2026

Beyond Waveform Robustness: Robust Feature-Vocoder Adversarial Attacks on Automatic Speech Recognition

Yifan Liao, Zongmin Zhang, Zhen Sun, Yuhui Sun +2 more

The paper introduces a novel Clean-Referenced Feature-Vocoder Attack, a black-box adversarial attack that perturbs high-level SSL feature representations instead of raw audio waveforms, achieving supe…

View →
cs.CRcs.SDeess.ASRecentMay 18, 2026

Escaping the Linearity Trap: Manifold Detours for Black-Box Adversarial Attacks on Singing Audio Deepfake Detection

Yifan Liao, Yule Liu, Zhen Sun, Zongmin Zhang +4 more

The paper introduces MARS, a novel meta-adversarial framework that significantly improves black-box adversarial attacks against state-of-the-art Singing Voice Deepfake Detection (SVDD) systems by esca…

View →
cs.CRcs.CVRecentMay 7, 2026

Stego Battlefield: Evaluating Image Steganography Attacks and Steganalysis Defenses

Zhen Sun, Zongmin Zhang, Leyi Sheng, Yule Liu +6 more

The paper introduces SADBench, a systematic benchmark designed to evaluate both the effectiveness of steganographic attacks injecting harmful content and the robustness of steganalysis defenses agains…

View →