Towards Characterizing Adversarial Defects of Deep Learning Software from the Lens of Uncertainty

24 April 2020

Yang Liu

Meng Sun

Papers citing "Towards Characterizing Adversarial Defects of Deep Learning Software from the Lens of Uncertainty"

21 / 21 papers shown

Title
Relationship between Uncertainty in DNNs and Adversarial Attacks Abigail Adeniran Adewale Adeyemo Adewale Adeyemo AAML 20 0 0 20 Sep 2024
Online Safety Analysis for LLMs: a Benchmark, an Assessment, and a Path Forward Xuan Xie Jiayang Song Zhehua Zhou Yuheng Huang Da Song Lei Ma OffRL 53 6 0 12 Apr 2024
An Empirical Study on Bugs Inside PyTorch: A Replication Study Sharon Chee Yin Ho Vahid Majdinasab Mohayeminul Islam D. Costa Emad Shihab Foutse Khomh Sarah Nadi Muhammad Raza 4 6 0 25 Jul 2023
An investigation of challenges encountered when specifying training data and runtime monitors for safety critical ML applications Hans-Martin Heyn E. Knauss Iswarya Malleswaran Shruthi Dinakaran 32 4 0 31 Jan 2023
When and Why Test Generators for Deep Learning Produce Invalid Inputs: an Empirical Study Vincenzo Riccio Paolo Tonella AAML 24 29 0 21 Dec 2022
Uncertainty Quantification for Deep Neural Networks: An Empirical Comparison and Usage Guidelines Michael Weiss Paolo Tonella BDL UQCV 22 11 0 14 Dec 2022
Beyond Voxel Prediction Uncertainty: Identifying brain lesions you can trust Benjamin Lambert Florence Forbes Senan Doyle A. Tucholka M. Dojat UQCV MedIm 14 6 0 22 Sep 2022
Generating and Detecting True Ambiguity: A Forgotten Danger in DNN Supervision Testing Michael Weiss A. Gómez Paolo Tonella AAML 18 6 0 21 Jul 2022
Simple Techniques Work Surprisingly Well for Neural Network Test Prioritization and Active Learning (Replicability Study) Michael Weiss Paolo Tonella AAML 15 49 0 02 May 2022
NPC: Neuron Path Coverage via Characterizing Decision Logic of Deep Neural Networks Xiaofei Xie Tianlin Li Jian-Xun Wang L. Ma Qing Guo Felix Juefei Xu Yang Liu AAML 18 50 0 24 Mar 2022
Security for Machine Learning-based Software Systems: a survey of threats, practices and challenges Huaming Chen Muhammad Ali Babar AAML 37 21 0 12 Jan 2022
DeepMetis: Augmenting a Deep Learning Test Set to Increase its Mutation Score Vincenzo Riccio Nargiz Humbatova Gunel Jahangirova Paolo Tonella 23 36 0 15 Sep 2021
Uncertainty-Wizard: Fast and User-Friendly Neural Network Uncertainty Quantification Michael Weiss Paolo Tonella UQCV 13 20 0 29 Dec 2020
A Software Engineering Perspective on Engineering Machine Learning Systems: State of the Art and Challenges G. Giray 33 120 0 14 Dec 2020
Stealing Deep Reinforcement Learning Models for Fun and Profit Kangjie Chen Shangwei Guo Tianwei Zhang Xiaofei Xie Yang Liu MLAU MIACV OffRL 24 45 0 09 Jun 2020
A Performance-Sensitive Malware Detection System Using Deep Learning on Mobile Devices Ruitao Feng Sen Chen Xiaofei Xie Guozhu Meng Shang-Wei Lin Yang Liu 36 103 0 11 May 2020
Who is Real Bob? Adversarial Attacks on Speaker Recognition Systems Guangke Chen Sen Chen Lingling Fan Xiaoning Du Zhe Zhao Fu Song Yang Liu AAML 17 193 0 03 Nov 2019
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 249 1,837 0 03 Feb 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 291 3,110 0 04 Nov 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,837 0 08 Jul 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015