Checkerboard: Closed-Form and Data-Independent Trigger Design for Clean-Label Backdoor Attacks

arXiv:2605.01298 · cs.CR, cs.CV · Submitted 2026-05-02 · Read on arXiv

cs.CR, cs.CV

Submitted: 2026-05-02

Updated: 2026-08-27

Terminology

• Accuracy — 18× in this paper · explained in 1 episode
• Complexity-driven Sample Selection — 9× in this paper
• Consistency — 8× in this paper · explained in 3 episodes
• Alternation — 6× in this paper · explained in 1 episode
• Transformer — 6× in this paper · explained in 2 episodes
• Attack Success Rate — 5× in this paper
• Provenance — 5× in this paper · explained in 3 episodes
• Robustness — 5× in this paper · explained in 5 episodes
• Benchmark — 4× in this paper · explained in 2 episodes
• Clustering — 4× in this paper · explained in 2 episodes
• Computer Vision and Pattern Recognition — 4× in this paper
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Spectral Signature — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Attack Success Rate (ASR) — 3× in this paper · explained in 2 episodes
• CVF International Conference on Computer Vision — 3× in this paper
• Convolutional Gradient Energy — 3× in this paper
• IEEE Symposium on Security and Privacy — 3× in this paper
• Latent Representation — 3× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Decoupling — 2× in this paper · explained in 2 episodes
• Distillation — 2× in this paper · explained in 2 episodes
• Feature Extraction — 2× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• International Conference on Learning Representations — 2× in this paper
• Network and Distributed System Security Symposium — 2× in this paper
• SIGSAC Conference on Computer and Communications Security — 2× in this paper
• Ablation Studies — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Continual Learning — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Fisher Discriminant Ratio — 1× in this paper
• Frequency-Domain Analysis — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• IEEE Transactions on Information Forensics and Security — 1× in this paper
• International Conference on Machine Learning — 1× in this paper
• Label Transfer Method — 1× in this paper
• Latent Representations — 1× in this paper · explained in 3 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes

Sources

• Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning
• An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
• BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain
• Escaping the Big Data Paradigm with Compact Transformers
• Very Deep Convolutional Networks for Large-Scale Image Recognition
• Label-Consistent Backdoor Attacks

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