mlsanityData to 14 Oct 2026

Backdoor Attacks on Deep Learning Face Detection

arXiv 2508.00620 ↗First posted 1 Aug 2025cs.CV cs.AI cs.CRcited by 0

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Abstract (arXiv)

Face Recognition Systems that operate in unconstrained environments capture images under varying conditions,such as inconsistent lighting, or diverse face poses. These challenges require including a Face Detection module that regresses bounding boxes and landmark coordinates for proper Face Alignment. This paper shows the effectiveness of Object Generation Attacks on Face Detection, dubbed Face Generation Attacks, and demonstrates for the first time a Landmark Shift Attack that backdoors the coordinate regression task performed by face detectors. We then offer mitigations against these vulnerabilities.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 18 of its 32 references that are in the map. First posted on arXiv 1 Aug 2025.

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18 of 32 references.

References · 18

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  3. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,639
  4. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,852
  5. 2018MobileNetV2: Inverted Residuals and Linear Bottleneckscited by 4,795
  6. 2014Deep Learning Face Attributes in the Wildcited by 3,693
  7. 2015SSD: Single Shot MultiBox Detectorcited by 3,130
  8. 2013Rich feature hierarchies for accurate object detection and semantic segmentationcited by 2,162
  9. 2017BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chaincited by 1,106
  10. 2016Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networkscited by 903
  11. 2015WIDER FACE: A Face Detection Benchmarkcited by 298
  12. 2019Label-Consistent Backdoor Attackscited by 296
6 more
  1. 2019A new Backdoor Attack in CNNs by training set corruption without label poisoningcited by 242
  2. 2020CelebA-Spoof: Large-Scale Face Anti-Spoofing Dataset with Rich Annotationscited by 109
  3. 2022BadDet: Backdoor Attacks on Object Detectioncited by 45
  4. 2021Subnet Replacement: Deployment-stage backdoor attack against deep neural networks in gray-box settingcited by 21
  5. 2023Attacking by Aligning: Clean-Label Backdoor Attacks on Object Detectioncited by 11
  6. 2024Mask-based Invisible Backdoor Attacks on Object Detectioncited by 3

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  1. 2025SoK: On the Survivability of Backdoor Attacks on Unconstrained Face Recognition Systems
  2. 2024Rethinking the Vulnerabilities of Face Recognition Systems:From a Practical Perspective
  3. 2024Countering Backdoor Attacks in Image Recognition: A Survey and Evaluation of Mitigation Strategies
  4. 2022Just Rotate it: Deploying Backdoor Attacks via Rotation Transformation
  5. 2025Backdoor Poisoning Attack Against Face Spoofing Attack Detection Methods
  6. 2022An anomaly detection approach for backdoored neural networks: face recognition as a case study
  7. 2022Resurrecting Trust in Facial Recognition: Mitigating Backdoor Attacks in Face Recognition to Prevent Potential Privacy Breaches
  8. 2022Untargeted Backdoor Attack against Object Detection