SoK: Certified Robustness for Deep Neural Networks-Reference-Cited by-同舟云学术

SoK: Certified Robustness for Deep Neural Networks

Author:

Li Linyi¹,Xie Tao²,Li Bo¹

Affiliation:

1. University of Illinois Urbana-Champaign

2. MoE (Peking University),Key Laboratory of High Confidence Software Technologies

Publisher

IEEE

Link

Reference222 articles.

1. Embedding symbolic knowledge into deep networks;xie;Advances in neural information processing systems,2019

2. Formal security analysis of neural networks using symbolic intervals;wang;27th USENIX Security Symposium (USENIX Security 18),2018

3. Efficient probabilistic logic reasoning with graph neural networks;zhang;International Conference on Learning Representations,2019

4. Neural network branching for neural network verification;lu;International Conference on Learning Representations,2020

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1. Certifiers Make Neural Networks Vulnerable to Availability Attacks;Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security;2023-11-26

2. On Audit and Certification of Machine Learning Systems;2023 34th Conference of Open Innovations Association (FRUCT);2023-11-15

3. MDTD: A Multi-Domain Trojan Detector for Deep Neural Networks;Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security;2023-11-15

4. CARE: Certifiably Robust Learning with Reasoning via Variational Inference;2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML);2023-02