A TTP by TTP Approach: Precise Malware Detection via Malicious TTP Recognition
Read the original on arXiv AI →The Flow has not summarised this story yet — read it at arXiv AI.
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The paper demonstrates that a single poisoned data point can successfully create a backdoor in linear models and ReLU neural networks without needing detailed knowledge of the training data. It establishes provable conditions under which this one‑poison attack works with high probability, achieving zero backdooring error while leaving the model’s normal performance largely unaffected. The attack relies only on coarse geometric bounds of the input space and training parameters.