Towards the Science of Security and Privacy in Machine Learning

11 November 2016

Papers citing "Towards the Science of Security and Privacy in Machine Learning"

50 / 88 papers shown

Title
VeriSplit: Secure and Practical Offloading of Machine Learning Inferences across IoT Devices Han Zhang Zifan Wang Mihir Dhamankar Matt Fredrikson Yuvraj Agarwal 49 2 0 02 Jun 2024
Data Reconstruction Attacks and Defenses: A Systematic Evaluation Sheng Liu Zihan Wang Yuxiao Chen Qi Lei AAML MIACV 61 4 0 13 Feb 2024
A Survey of Graph Unlearning Anwar Said Tyler Derr Mudassir Shabbir W. Abbas X. Koutsoukos MU 33 7 0 23 Aug 2023
Runtime Stealthy Perception Attacks against DNN-based Adaptive Cruise Control Systems Xugui Zhou Anqi Chen Maxfield Kouzel Haotian Ren Morgan McCarty Cristina Nita-Rotaru H. Alemzadeh AAML 31 2 0 18 Jul 2023
Data Minimization at Inference Time Cuong Tran Ferdinando Fioretto 33 1 0 27 May 2023
Patchwork Learning: A Paradigm Towards Integrative Analysis across Diverse Biomedical Data Sources Suraj Rajendran Weishen Pan M. Sabuncu Yong Chen Jiayu Zhou Fei Wang 59 14 0 10 May 2023
Federated Learning of Shareable Bases for Personalization-Friendly Image Classification Hong-You Chen Shitian Zhao Ruotong Wang Xuhui Jia Qi Boqing Gong Wei-Lun Chao Li Zhang FedML 30 7 0 16 Apr 2023
Personalized Privacy Auditing and Optimization at Test Time Cuong Tran Ferdinando Fioretto 11 2 0 31 Jan 2023
Backdoor Attacks Against Dataset Distillation Yugeng Liu Zheng Li Michael Backes Yun Shen Yang Zhang DD 42 28 0 03 Jan 2023
Federated Learning for Healthcare Domain - Pipeline, Applications and Challenges Madhura Joshi Ankit Pal Malaikannan Sankarasubbu OOD AI4CE FedML 25 93 0 15 Nov 2022
Adversarial Robustness for Tabular Data through Cost and Utility Awareness Klim Kireev B. Kulynych Carmela Troncoso AAML 26 16 0 27 Aug 2022
Membership-Doctor: Comprehensive Assessment of Membership Inference Against Machine Learning Models Xinlei He Zheng Li Weilin Xu Cory Cornelius Yang Zhang MIACV 38 24 0 22 Aug 2022
Lifelong DP: Consistently Bounded Differential Privacy in Lifelong Machine Learning Phung Lai Han Hu Nhathai Phan Ruoming Jin My T. Thai An M. Chen 25 2 0 26 Jul 2022
Careful What You Wish For: on the Extraction of Adversarially Trained Models Kacem Khaled Gabriela Nicolescu F. Magalhães MIACV AAML 35 4 0 21 Jul 2022
DIMBA: Discretely Masked Black-Box Attack in Single Object Tracking Xiangyu Yin Wenjie Ruan J. Fieldsend AAML 38 28 0 17 Jul 2022
Never trust, always verify : a roadmap for Trustworthy AI? L. Tidjon Foutse Khomh 41 15 0 23 Jun 2022
Architectural Backdoors in Neural Networks Mikel Bober-Irizar Ilia Shumailov Yiren Zhao Robert D. Mullins Nicolas Papernot AAML 23 23 0 15 Jun 2022
Do You Think You Can Hold Me? The Real Challenge of Problem-Space Evasion Attacks Harel Berger A. Dvir Chen Hajaj Rony Ronen AAML 29 3 0 09 May 2022
Federated Learning with Noisy User Feedback Rahul Sharma Anil Ramakrishna Ansel MacLaughlin Anna Rumshisky Jimit Majmudar Clement Chung Salman Avestimehr Rahul Gupta FedML 23 10 0 06 May 2022
Robustness Testing of Data and Knowledge Driven Anomaly Detection in Cyber-Physical Systems Xugui Zhou Maxfield Kouzel H. Alemzadeh OOD AAML 8 13 0 20 Apr 2022
Efficient Attribute Unlearning: Towards Selective Removal of Input Attributes from Feature Representations Tao Guo Song Guo Jiewei Zhang Wenchao Xu Junxiao Wang MU 29 18 0 27 Feb 2022
A Tutorial on Adversarial Learning Attacks and Countermeasures Cato Pauling Michael Gimson Muhammed Qaid Ahmad Kida Basel Halak AAML 25 11 0 21 Feb 2022
Security for Machine Learning-based Software Systems: a survey of threats, practices and challenges Huaming Chen Muhammad Ali Babar AAML 42 22 0 12 Jan 2022
Adversarial Attacks Against Deep Generative Models on Data: A Survey Hui Sun Tianqing Zhu Zhiqiu Zhang Dawei Jin Wanlei Zhou AAML 47 42 0 01 Dec 2021
Bandwidth Utilization Side-Channel on ML Inference Accelerators Sarbartha Banerjee Shijia Wei Prakash Ramrakhyani Mohit Tiwari 23 3 0 14 Oct 2021
Label Noise in Adversarial Training: A Novel Perspective to Study Robust Overfitting Chengyu Dong Liyuan Liu Jingbo Shang NoLa AAML 66 18 0 07 Oct 2021
Membership Inference Attacks Against Recommender Systems Minxing Zhang Z. Ren Zihan Wang Pengjie Ren Zhumin Chen Pengfei Hu Yang Zhang MIACV AAML 26 83 0 16 Sep 2021
Federated Learning Versus Classical Machine Learning: A Convergence Comparison Muhammad Asad Ahmed Moustafa Takayuki Ito FedML 30 42 0 22 Jul 2021
Bad Characters: Imperceptible NLP Attacks Nicholas Boucher Ilia Shumailov Ross J. Anderson Nicolas Papernot AAML SILM 41 103 0 18 Jun 2021
Membership Inference Attacks on Machine Learning: A Survey Hongsheng Hu Z. Salcic Lichao Sun Gillian Dobbie Philip S. Yu Xuyun Zhang MIACV 35 412 0 14 Mar 2021
Proof-of-Learning: Definitions and Practice Hengrui Jia Mohammad Yaghini Christopher A. Choquette-Choo Natalie Dullerud Anvith Thudi Varun Chandrasekaran Nicolas Papernot AAML 25 99 0 09 Mar 2021
Guided Interpolation for Adversarial Training Chen Chen Jingfeng Zhang Xilie Xu Tianlei Hu Gang Niu Gang Chen Masashi Sugiyama AAML 32 10 0 15 Feb 2021
Resilient Machine Learning for Networked Cyber Physical Systems: A Survey for Machine Learning Security to Securing Machine Learning for CPS Felix O. Olowononi D. Rawat Chunmei Liu 38 133 0 14 Feb 2021
Quantifying and Mitigating Privacy Risks of Contrastive Learning Xinlei He Yang Zhang 21 51 0 08 Feb 2021
Understanding the Interaction of Adversarial Training with Noisy Labels Jianing Zhu Jingfeng Zhang Bo Han Tongliang Liu Gang Niu Hongxia Yang Mohan Kankanhalli Masashi Sugiyama AAML 27 27 0 06 Feb 2021
ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models Yugeng Liu Rui Wen Xinlei He A. Salem Zhikun Zhang Michael Backes Emiliano De Cristofaro Mario Fritz Yang Zhang AAML 17 125 0 04 Feb 2021
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead Muhammad Shafique Mahum Naseer T. Theocharides C. Kyrkou O. Mutlu Lois Orosa Jungwook Choi OOD 81 100 0 04 Jan 2021
A Survey of Machine Learning Techniques in Adversarial Image Forensics Ehsan Nowroozi Ali Dehghantanha R. Parizi K. Choo AAML 25 72 0 19 Oct 2020
Geometry-aware Instance-reweighted Adversarial Training Jingfeng Zhang Jianing Zhu Gang Niu Bo Han Masashi Sugiyama Mohan Kankanhalli AAML 47 269 0 05 Oct 2020
Membership Leakage in Label-Only Exposures Zheng Li Yang Zhang 34 237 0 30 Jul 2020
SoK: The Faults in our ASRs: An Overview of Attacks against Automatic Speech Recognition and Speaker Identification Systems H. Abdullah Kevin Warren Vincent Bindschaedler Nicolas Papernot Patrick Traynor AAML 32 128 0 13 Jul 2020
Reducing Risk of Model Inversion Using Privacy-Guided Training Abigail Goldsteen Gilad Ezov Ariel Farkash 30 4 0 29 Jun 2020
Neural Anisotropy Directions Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard 34 16 0 17 Jun 2020
Sponge Examples: Energy-Latency Attacks on Neural Networks Ilia Shumailov Yiren Zhao Daniel Bates Nicolas Papernot Robert D. Mullins Ross J. Anderson SILM 19 127 0 05 Jun 2020
When Machine Unlearning Jeopardizes Privacy Min Chen Zhikun Zhang Tianhao Wang Michael Backes Mathias Humbert Yang Zhang MIACV 31 218 0 05 May 2020
An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies David Enthoven Zaid Al-Ars FedML 60 50 0 01 Apr 2020
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness Ahmadreza Jeddi M. Shafiee Michelle Karg C. Scharfenberger A. Wong OOD AAML 72 63 0 02 Mar 2020
The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization Yifei Min Lin Chen Amin Karbasi AAML 37 69 0 25 Feb 2020
Adversarial Machine Learning -- Industry Perspectives Ramnath Kumar Magnus Nyström J. Lambert Andrew Marshall Mario Goertzel Andi Comissoneru Matt Swann Sharon Xia AAML SILM 29 232 0 04 Feb 2020
MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius Runtian Zhai Chen Dan Di He Huan Zhang Boqing Gong Pradeep Ravikumar Cho-Jui Hsieh Liwei Wang OOD AAML 21 177 0 08 Jan 2020