Finding needles in a haystack: A Black-Box Approach to Invisible Watermark Detection

no code implementations • 23 Mar 2024 • Minzhou Pan, Zhenting Wang, Xin Dong, Vikash Sehwag, Lingjuan Lyu, Xue Lin

In this paper, we propose WaterMark Detection (WMD), the first invisible watermark detection method under a black-box and annotation-free setting.

ASSET: Robust Backdoor Data Detection Across a Multiplicity of Deep Learning Paradigms

1 code implementation • 22 Feb 2023 • Minzhou Pan, Yi Zeng, Lingjuan Lyu, Xue Lin, Ruoxi Jia

However, we lack a thorough understanding of the applicability of existing detection methods across a variety of learning settings.

backdoor defense Self-Supervised Learning +1

How to Sift Out a Clean Data Subset in the Presence of Data Poisoning?

1 code implementation • 12 Oct 2022 • Yi Zeng, Minzhou Pan, Himanshu Jahagirdar, Ming Jin, Lingjuan Lyu, Ruoxi Jia

Most poisoning defenses presume access to a set of clean data (or base set).

Bilevel Optimization Data Poisoning

Narcissus: A Practical Clean-Label Backdoor Attack with Limited Information

2 code implementations • 11 Apr 2022 • Yi Zeng, Minzhou Pan, Hoang Anh Just, Lingjuan Lyu, Meikang Qiu, Ruoxi Jia

With poisoning equal to or less than 0. 5% of the target-class data and 0. 05% of the training set, we can train a model to classify test examples from arbitrary classes into the target class when the examples are patched with a backdoor trigger.

Backdoor Attack Clean-label Backdoor Attack (0.024%) +1