Semantic Adversarial Deep Learning

19 April 2018

Papers citing "Semantic Adversarial Deep Learning"

45 / 45 papers shown

Title
Incorporating System-level Safety Requirements in Perception Models via Reinforcement Learning Weisi Fan Jesse Lane Qisai Liu S. Sarkar Tichakorn Wongpiromsarn 72 0 0 04 Dec 2024
Pixel-wise Smoothing for Certified Robustness against Camera Motion Perturbations Hanjiang Hu Zuxin Liu Linyi Li Jiacheng Zhu Ding Zhao 30 0 0 22 Sep 2023
Multi-objective Evolutionary Search of Variable-length Composite Semantic Perturbations Jialiang Sun Wen Yao Tingsong Jiang Xiaoqian Chen AAML 23 0 0 13 Jul 2023
Evaluation Metrics for Object Detection for Autonomous Systems Apurva Badithela Tichakorn Wongpiromsarn R. Murray 21 3 0 19 Oct 2022
Testing Rare Downstream Safety Violations via Upstream Adaptive Sampling of Perception Error Models Craig Innes S. Ramamoorthy AAML 17 13 0 20 Sep 2022
Provable Defense Against Geometric Transformations Rem Yang Jacob S. Laurel Sasa Misailovic Gagandeep Singh AAML 25 15 0 22 Jul 2022
SoK: On the Semantic AI Security in Autonomous Driving Junjie Shen Ningfei Wang Ziwen Wan Yunpeng Luo Takami Sato ... Zhenyu Zhong Kang Li Ziming Zhao Chunming Qiao Qi Alfred Chen AAML 15 39 0 10 Mar 2022
Safe AI -- How is this Possible? Harald Ruess Simon Burton 11 0 0 25 Jan 2022
Local Repair of Neural Networks Using Optimization K. Majd Siyu Zhou H. B. Amor Georgios Fainekos S. Sankaranarayanan 13 6 0 28 Sep 2021
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 32 16 0 20 Sep 2021
Automated Testing with Temporal Logic Specifications for Robotic Controllers using Adaptive Experiment Design Craig Innes S. Ramamoorthy 22 5 0 16 Sep 2021
On the Exploitability of Audio Machine Learning Pipelines to Surreptitious Adversarial Examples Adelin Travers Lorna Licollari Guanghan Wang Varun Chandrasekaran Adam Dziedzic David Lie Nicolas Papernot AAML 20 3 0 03 Aug 2021
Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Challenges and Solutions Eike Petersen Yannik Potdevin Esfandiar Mohammadi Stephan Zidowitz Sabrina Breyer ... Sandra Henn Ludwig Pechmann M. Leucker P. Rostalski Christian Herzog FaML AILaw OOD 27 21 0 20 Jul 2021
Exposing Previously Undetectable Faults in Deep Neural Networks Isaac Dunn Hadrien Pouget Daniel Kroening T. Melham AAML 26 28 0 01 Jun 2021
Security and Privacy in the Emerging Cyber-Physical World: A Survey Zhiyuan Yu Zack Kaplan Qiben Yan Ning Zhang 11 31 0 27 May 2021
Leveraging Classification Metrics for Quantitative System-Level Analysis with Temporal Logic Specifications Apurva Badithela Tichakorn Wongpiromsarn R. Murray 20 9 0 16 May 2021
Software Engineering for AI-Based Systems: A Survey Silverio Martínez-Fernández Justus Bogner Xavier Franch Marc Oriol Julien Siebert Adam Trendowicz Anna Maria Vollmer Stefan Wagner 19 211 0 05 May 2021
Mitigating the Impact of Adversarial Attacks in Very Deep Networks Mohammed Hassanin Ibrahim Radwan Nour Moustafa M. Tahtali Neeraj Kumar AAML 11 5 0 08 Dec 2020
Scenic: A Language for Scenario Specification and Data Generation Daniel J. Fremont Edward J. Kim T. Dreossi Shromona Ghosh Xiangyu Yue Alberto L. Sangiovanni-Vincentelli S. Seshia 27 97 0 13 Oct 2020
Deep Learning & Software Engineering: State of Research and Future Directions P. Devanbu Matthew B. Dwyer Sebastian G. Elbaum M. Lowry Kevin Moran Denys Poshyvanyk Baishakhi Ray Rishabh Singh Xiangyu Zhang 11 22 0 17 Sep 2020
Certifying Decision Trees Against Evasion Attacks by Program Analysis Stefano Calzavara Pietro Ferrara Claudio Lucchese AAML 11 10 0 06 Jul 2020
Model-Based Robust Deep Learning: Generalizing to Natural, Out-of-Distribution Data Alexander Robey Hamed Hassani George J. Pappas OOD 35 42 0 20 May 2020
Formal Analysis and Redesign of a Neural Network-Based Aircraft Taxiing System with VerifAI Daniel J. Fremont Johnathan Chiu D. Margineantu Denis Osipychev S. Seshia 23 53 0 14 May 2020
Metrics and methods for robustness evaluation of neural networks with generative models Igor Buzhinsky Arseny Nerinovsky S. Tripakis AAML 34 25 0 04 Mar 2020
Cost-Aware Robust Tree Ensembles for Security Applications Yizheng Chen Shiqi Wang Weifan Jiang Asaf Cidon Suman Jana AAML OOD 12 5 0 03 Dec 2019
Counterexample-Guided Synthesis of Perception Models and Control Shromona Ghosh Yash Vardhan Pant H. Ravanbakhsh S. Seshia 18 14 0 04 Nov 2019
Attacking Vision-based Perception in End-to-End Autonomous Driving Models Adith Boloor Karthik Garimella Xin He C. Gill Yevgeniy Vorobeychik Xuan Zhang AAML 15 104 0 02 Oct 2019
Analyzing and Improving Neural Networks by Generating Semantic Counterexamples through Differentiable Rendering Lakshya Jain Varun Chandrasekaran Uyeong Jang Wilson Wu Andrew Lee Andy Yan Steven Chen S. Jha S. Seshia AAML 13 11 0 02 Oct 2019
Requirements-driven Test Generation for Autonomous Vehicles with Machine Learning Components Cumhur Erkan Tuncali Georgios Fainekos Danil Prokhorov Hisahiro Ito J. Kapinski 14 105 0 02 Aug 2019
Securing Connected & Autonomous Vehicles: Challenges Posed by Adversarial Machine Learning and The Way Forward A. Qayyum Muhammad Usama Junaid Qadir Ala I. Al-Fuqaha AAML 19 187 0 29 May 2019
Rearchitecting Classification Frameworks For Increased Robustness Varun Chandrasekaran Brian Tang Nicolas Papernot Kassem Fawaz S. Jha Xi Wu AAML OOD 27 8 0 26 May 2019
Assuring the Machine Learning Lifecycle: Desiderata, Methods, and Challenges Rob Ashmore R. Calinescu Colin Paterson AI4TS 21 116 0 10 May 2019
Towards Analyzing Semantic Robustness of Deep Neural Networks Abdullah Hamdi Bernard Ghanem AAML 25 17 0 09 Apr 2019
On Training Robust PDF Malware Classifiers Yizheng Chen Shiqi Wang Dongdong She Suman Jana AAML 40 67 0 06 Apr 2019
A Formalization of Robustness for Deep Neural Networks T. Dreossi Shromona Ghosh Alberto L. Sangiovanni-Vincentelli S. Seshia GAN 8 30 0 24 Mar 2019
Simple Physical Adversarial Examples against End-to-End Autonomous Driving Models Adith Boloor Xin He C. Gill Yevgeniy Vorobeychik Xuan Zhang AAML 13 74 0 12 Mar 2019
VERIFAI: A Toolkit for the Design and Analysis of Artificial Intelligence-Based Systems T. Dreossi Daniel J. Fremont Shromona Ghosh Edward J. Kim H. Ravanbakhsh Marcell Vazquez-Chanlatte S. Seshia 13 29 0 12 Feb 2019
Cost-Sensitive Robustness against Adversarial Examples Xiao Zhang David E. Evans AAML 21 25 0 22 Oct 2018
Verification for Machine Learning, Autonomy, and Neural Networks Survey Weiming Xiang Patrick Musau A. Wild Diego Manzanas Lopez Nathaniel P. Hamilton Xiaodong Yang Joel A. Rosenfeld Taylor T. Johnson 22 101 0 03 Oct 2018
Scenic: A Language for Scenario Specification and Scene Generation Daniel J. Fremont T. Dreossi Shromona Ghosh Xiangyu Yue Alberto L. Sangiovanni-Vincentelli S. Seshia 34 245 0 25 Sep 2018
Counterexample-Guided Data Augmentation T. Dreossi Shromona Ghosh Xiangyu Yue Kurt Keutzer Alberto L. Sangiovanni-Vincentelli S. Seshia AAML 8 61 0 17 May 2018
Simulation-based Adversarial Test Generation for Autonomous Vehicles with Machine Learning Components Cumhur Erkan Tuncali Georgios Fainekos Hisahiro Ito J. Kapinski 17 182 0 18 Apr 2018
Compositional Falsification of Cyber-Physical Systems with Machine Learning Components T. Dreossi Alexandre Donzé S. Seshia AAML 22 230 0 02 Mar 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 228 1,837 0 03 Feb 2017
Safety Verification of Deep Neural Networks Xiaowei Huang M. Kwiatkowska Sen Wang Min Wu AAML 180 932 0 21 Oct 2016