# Adversarial Light Projection Attacks on Face Recognition Systems: A Feasibility Study

arXiv: https://arxiv.org/abs/2003.11145 · HTML: https://mlsanity.com/paper/2003.11145/

## Key facts

- Cited by 40 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Mar 2020.

## Built on by (most cited first, 30 of 40)

- [Advances in adversarial attacks and defenses in computer vision: A survey](https://mlsanity.com/paper/2108.00401/) (2021)
- [Shadows can be Dangerous: Stealthy and Effective Physical-world Adversarial Attack by Natural Phenomenon](https://mlsanity.com/paper/2203.03818/) (2022)
- [Adversarial Sticker: A Stealthy Attack Method in the Physical World](https://mlsanity.com/paper/2104.06728/) (2021)
- [Adversarial Laser Beam: Effective Physical-World Attack to DNNs in a Blink](https://mlsanity.com/paper/2103.06504/) (2021)
- [Physical Adversarial Attack meets Computer Vision: A Decade Survey](https://mlsanity.com/paper/2209.15179/) (2022)
- [Optical Adversarial Attack](https://mlsanity.com/paper/2108.06247/) (2021)
- [A Survey on Physical Adversarial Attack in Computer Vision](https://mlsanity.com/paper/2209.14262/) (2022)
- [Physical-World Optical Adversarial Attacks on 3D Face Recognition](https://mlsanity.com/paper/2205.13412/) (2022)
- [Benchmarking Adversarial Patch Against Aerial Detection](https://mlsanity.com/paper/2210.16765/) (2022)
- [Physical Adversarial Attacks For Camera-based Smart Systems: Current Trends, Categorization, Applications, Research Challenges, and Future Outlook](https://mlsanity.com/paper/2308.06173/) (2023)
- [A Survey of Robustness and Safety of 2D and 3D Deep Learning Models Against Adversarial Attacks](https://mlsanity.com/paper/2310.00633/) (2023)
- [SoK: Anti-Facial Recognition Technology](https://mlsanity.com/paper/2112.04558/) (2021)
- [Rolling Colors: Adversarial Laser Exploits against Traffic Light Recognition](https://mlsanity.com/paper/2204.02675/) (2022)
- [Adversarial Laser Spot: Robust and Covert Physical-World Attack to DNNs](https://mlsanity.com/paper/2206.01034/) (2022)
- [Adversarial Color Film: Effective Physical-World Attack to DNNs](https://mlsanity.com/paper/2209.02430/) (2022)
- [Visual Adversarial Attacks and Defenses in the Physical World: A Survey](https://mlsanity.com/paper/2211.01671/) (2022)
- [State-of-the-art optical-based physical adversarial attacks for deep learning computer vision systems](https://mlsanity.com/paper/2303.12249/) (2023)
- [RSTAM: An Effective Black-Box Impersonation Attack on Face Recognition using a Mobile and Compact Printer](https://mlsanity.com/paper/2206.12590/) (2022)
- [CBA: Contextual Background Attack against Optical Aerial Detection in the Physical World](https://mlsanity.com/paper/2302.13519/) (2023)
- [Adversarial Neon Beam: A Light-based Physical Attack to DNNs](https://mlsanity.com/paper/2204.00853/) (2022)
- [Improving the Transferability of Adversarial Examples with New Iteration Framework and Input Dropout](https://mlsanity.com/paper/2106.01617/) (2021)
- [A Comprehensive Study on the Robustness of Image Classification and Object Detection in Remote Sensing: Surveying and Benchmarking](https://mlsanity.com/paper/2306.12111/) (2023)
- [Adversarial Zoom Lens: A Novel Physical-World Attack to DNNs](https://mlsanity.com/paper/2206.12251/) (2022)
- [Embodied Laser Attack:Leveraging Scene Priors to Achieve Agent-based Robust Non-contact Attacks](https://mlsanity.com/paper/2312.09554/) (2023)
- [A Survey on Physical Adversarial Attacks against Face Recognition Systems](https://mlsanity.com/paper/2410.16317/) (2024)
- [Why Don't You Clean Your Glasses? Perception Attacks with Dynamic Optical Perturbations](https://mlsanity.com/paper/2307.13131/) (2023)
- [Rethinking the Threat and Accessibility of Adversarial Attacks against Face Recognition Systems](https://mlsanity.com/paper/2407.08514/) (2024)
- [Non-Uniform Illumination Attack for Fooling Convolutional Neural Networks](https://mlsanity.com/paper/2409.03458/) (2024)
- [RAF: Recursive Adversarial Attacks on Face Recognition Using Extremely Limited Queries](https://mlsanity.com/paper/2207.01149/) (2022)
- [Adversarial Color Projection: A Projector-based Physical Attack to DNNs](https://mlsanity.com/paper/2209.09652/) (2022)

## Abstract (arXiv)

Deep learning-based systems have been shown to be vulnerable to adversarial attacks in both digital and physical domains. While feasible, digital attacks have limited applicability in attacking deployed systems, including face recognition systems, where an adversary typically has access to the input and not the transmission channel. In such setting, physical attacks that directly provide a malicious input through the input channel pose a bigger threat. We investigate the feasibility of conducting real-time physical attacks on face recognition systems using adversarial light projections. A setup comprising a commercially available web camera and a projector is used to conduct the attack. The adversary uses a transformation-invariant adversarial pattern generation method to generate a digital adversarial pattern using one or more images of the target available to the adversary. The digital adversarial pattern is then projected onto the adversary's face in the physical domain to either impersonate a target (impersonation) or evade recognition (obfuscation). We conduct preliminary experiments using two open-source and one commercial face recognition system on a pool of 50 subjects. Our experimental results demonstrate the vulnerability of face recognition systems to light projection attacks in both white-box and black-box attack settings.