Occlusion is a prevalent and easily realizable semantic perturbation to deep neural networks (DNNs). It can fool a DNN into misclassifying an input image by occluding some segments, possibly resulting in severe errors. Therefore, DNNs planted in safety-critical systems should be verified to be robust against occlusions prior to deployment. However, most existing robustness verification approaches for DNNs are focused on non-semantic perturbations and are not suited to the occlusion case. In this paper, we propose the first efficient, SMT-based approach for formally verifying the occlusion robustness of DNNs. We formulate the occlusion robustness verification problem and prove it is NP-complete. Then, we devise a novel approach for encoding occlusions as a part of neural networks and introduce two acceleration techniques so that the extended neural networks can be efficiently verified using off-the-shelf, SMT-based neural network verification tools. We implement our approach in a prototype called OccRob and extensively evaluate its performance on benchmark datasets with various occlusion variants. The experimental results demonstrate our approach’s effectiveness and efficiency in verifying DNNs’ robustness against various occlusions, and its ability to generate counterexamples when these DNNs are not robust.
|Original language||American English|
|Title of host publication||Tools and Algorithms for the Construction and Analysis of Systems - 29th International Conference, TACAS 2023, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022, Proceedings|
|Editors||Sriram Sankaranarayanan, Natasha Sharygina|
|Publisher||Springer Science and Business Media Deutschland GmbH|
|Number of pages||19|
|State||Published - 2023|
|Event||29th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2023, held as part of the 26th European Joint Conferences on Theory and Practice of Software, ETAPS 2023 - Paris, France|
Duration: 22 Apr 2023 → 27 Apr 2023
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||29th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2023, held as part of the 26th European Joint Conferences on Theory and Practice of Software, ETAPS 2023|
|Period||22/04/23 → 27/04/23|
Bibliographical notePublisher Copyright:
© 2023, The Author(s).