RAMP: Reversing Adversarial Perturbations to Strengthen Clean-Label Backdoor Attacks against Malware Detectors

arXiv:2609.27422 · cs.CR · Submitted 2026-09-23 · Read on arXiv

cs.CR

Submitted: 2026-09-23

Updated: 2026-09-23

Code: https://github.com/jinwenxin0001-gif/RAMP-Malware-Backdoor

Terminology

• Consistency — 14× in this paper · explained in 3 episodes
• Fine-Tuning — 12× in this paper · explained in 5 episodes
• Pruning — 9× in this paper · explained in 4 episodes
• Accuracy — 7× in this paper · explained in 1 episode
• Ablation — 5× in this paper · explained in 1 episode
• Ablation study — 4× in this paper · explained in 1 episode
• Alignment — 3× in this paper · explained in 1 episode
• Attack Success Rate — 2× in this paper
• Attack Success Rate (ASR) — 2× in this paper · explained in 2 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Core — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Adversarial Attacks — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Clean Data Accuracy — 1× in this paper
• Concept Drift — 1× in this paper · explained in 4 episodes
• Distribution Shift — 1× in this paper · explained in 6 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Feature Engineering — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Structural Constraints — 1× in this paper · explained in 2 episodes
• Structural Integrity — 1× in this paper · explained in 3 episodes
• Verification — 1× in this paper · explained in 2 episodes
• Windows Portable Executable — 1× in this paper

Sources

• EMBER: An Open Dataset for Training Static PE Malware Machine Learning Models
• SOREL-20M: A Large Scale Benchmark Dataset for Malicious PE Detection
• Being Single Has Benefits. Instance Poisoning to Deceive Malware Classifiers
• Label-Consistent Backdoor Attacks

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