Papers › Towards Verifying Robustness of Neural Networks Against Semantic Perturbations

Towards Verifying Robustness of Neural Networks Against Semantic Perturbations

19 Dec 2019arXiv:1912.09533archive 2025-07-28

Jeet Mohapatra, Tsui-Wei, Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel

Verifying robustness of neural networks given a specified threat model is a fundamental yet challenging task. While current verification methods mainly focus on the ℓₚ-norm threat model of the input instances, robustness verification against semantic adversarial attacks inducing large ℓₚ-norm perturbations, such as color shifting and lighting adjustment, are beyond their capacity. To bridge this gap, we propose \textit{Semantify-NN}, a model-agnostic and generic robustness verification approach against semantic perturbations for neural networks. By simply inserting our proposed \textit{semantic perturbation layers} (SP-layers) to the input layer of any given model, \textit{Semantify-NN} is model-agnostic, and any ℓₚ-norm based verification tools can be used to verify the model robustness against semantic perturbations. We illustrate the principles of designing the SP-layers and provide examples including semantic perturbations to image classification in the space of hue, saturation, lightness, brightness, contrast and rotation, respectively. In addition, an efficient refinement technique is proposed to further significantly improve the semantic certificate. Experiments on various network architectures and different datasets demonstrate the superior verification performance of \textit{Semantify-NN} over ℓₚ-norm-based verification frameworks that naively convert semantic perturbation to ℓₚ-norm. The results show that \textit{Semantify-NN} can support robustness verification against a wide range of semantic perturbations. Code available https://github.com/JeetMo/Semantify-NN

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gen_image JeetMo/Semantify-NN/main_attack.py official repository unverified MIT (permissive) · 2dc5034ca17fd4bd · report
get_first_layers JeetMo/Semantify-NN/threat_models/threat_bandc.py official repository unverified MIT (permissive) · a4d2f938720b56d4 · report
get_first_layers JeetMo/Semantify-NN/threat_models/threat_hue.py official repository unverified MIT (permissive) · d0116430981ceec3 · report
get_first_layers JeetMo/Semantify-NN/threat_models/threat_lighten.py official repository unverified MIT (permissive) · 5e205a469e2f1f44 · report
get_first_layers JeetMo/Semantify-NN/threat_models/threat_saturate.py official repository unverified MIT (permissive) · 62ca2ee8e41b356b · report
get_first_layers_cnn JeetMo/Semantify-NN/threat_models/threat_bandc.py official repository unverified MIT (permissive) · 425759c9c3bffdaf · report
get_first_layers_cnn JeetMo/Semantify-NN/threat_models/threat_hue.py official repository unverified MIT (permissive) · 8c54db56cb682eb8 · report
get_first_layers_cnn JeetMo/Semantify-NN/threat_models/threat_lighten.py official repository unverified MIT (permissive) · 2b3f7bdf9b590e8d · report
get_first_layers_cnn JeetMo/Semantify-NN/threat_models/threat_saturate.py official repository unverified MIT (permissive) · 64afcfd2156e3509 · report
handle_parser JeetMo/Semantify-NN/main_attack.py official repository unverified MIT (permissive) · 67bd753068aa89ba · report
handle_parser JeetMo/Semantify-NN/main_semantic_hsl.py official repository unverified MIT (permissive) · 5cbc3c9756e510c7 · report
handle_parser JeetMo/Semantify-NN/main_semantic_rotate.py official repository unverified MIT (permissive) · 7872e4a763ce993f · report
loss JeetMo/Semantify-NN/utils/save_nlayer_weights.py official repository unverified MIT (permissive) · cccee9750469bb0a · report
sigmoid JeetMo/Semantify-NN/utils/activations.py official repository unverified MIT (permissive) · 54fb221cde340265 · report
sigmoidd JeetMo/Semantify-NN/utils/activations.py official repository unverified MIT (permissive) · dfab2f10bd0e8f01 · report
sigmoidid JeetMo/Semantify-NN/utils/activations.py official repository unverified MIT (permissive) · fca193ce378f2c1e · report

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Image Classificationimage-classification

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