arXiv AI November 5, 2026 By Quentin Le Roux, Marti Jimenez, Yannick Teglia, Philippe Loubet Moundi

A Bag of Tricks for Defending Deep Learning-based Face Recognition Pipelines against Backdoor Attacks

The paper presents three practical defense tricks to protect deep learning-based face recognition pipelines from backdoor attacks that arise when training data is sourced from potentially compromised third parties. The first trick operates during training to detect poisoned identities before deployment, while the other two work at inference time to filter suspicious inputs. Each method is described with its motivation, algorithm, computational impact, and evaluated on realistic face recognition workloads.

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arXiv AI

Aug 3

Have I Seen You? Embedding Behavior Signals Synthetic Face Dataset Membership

arXiv:2607. 29144v1 Announce Type: cross Abstract: Synthetic face datasets are increasingly used to reduce privacy exposure and data access constraints in biometric recognition.

By Pawe{\l} Borsukiewicz, Daniele Lunghi, Wendk\^uuni C. Ou\'edraogo, Jacques Klein, Tegawend\'e F. Bissyand\'e

rag safety

arXiv AI

Aug 3

DiffAttack: Evasion Attacks Against Face Recognition via Latent Diffusion Models

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By Omid Ahmadieh, Nima Karimian

rag diffusion benchmarks safety

arXiv Computer Vision

Oct 21

Only Train Once: Uncertainty-Aware One-Class Learning for Face Authenticity Detection

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By Qingchao Jiang, Zhenxuan Hou, Zhiying Zhu, Zhenxing Qian, Xinpeng Zhang, Zaiwang Gu

rag benchmarks

Hugging Face Trending Papers

Jul 6

Statistical Adversaries: Natural Backdoor-like Features in Vision Datasets

Model-specific adversarial attacks have been extensively studied. We study a different failure mode: naturally occurring statistical signals in vision data that can behave like backdoor-like triggers without being maliciously inserted.

safety

arXiv Machine Learning

Oct 12

RPP: A Certified Poisoned-Sample Detection Framework for Backdoor Attacks under Dataset Imbalance

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By Miao Lin, Feng Yu, Rui Ning, Lusi Li, Jiawei Chen, Qian Lou, Mengxin Zheng, Chunsheng Xin, Hongyi Wu

benchmarks safety

arXiv Machine Learning

Sep 22

StyleAT: Defending Face Recognition Against Semantic Attacks

arXiv:2609.23596v1 Announce Type: cross Abstract: With face-recognition models now embedded in everyday authentication and surveillance, recent works have pinpointed a critical weakness: these models...

By Ben Shapira, Roi Cohen, Shang-Tse Chen, Mahmood Sharif

diffusion benchmarks safety