Stealing Hyperparameters in Machine Learning

14 February 2018

Papers citing "Stealing Hyperparameters in Machine Learning"

50 / 206 papers shown

Title
Practical Defences Against Model Inversion Attacks for Split Neural Networks Tom Titcombe A. Hall Pavlos Papadopoulos Daniele Romanini FedML 27 58 0 12 Apr 2021
Machine Learning Based Cyber Attacks Targeting on Controlled Information: A Survey Yuantian Miao Chao Chen Lei Pan Qing-Long Han Jun Zhang Yang Xiang AAML 49 68 0 16 Feb 2021
Membership Inference Attacks are Easier on Difficult Problems Avital Shafran Shmuel Peleg Yedid Hoshen MIACV 14 16 0 15 Feb 2021
Dompteur: Taming Audio Adversarial Examples Thorsten Eisenhofer Lea Schonherr Joel Frank Lars Speckemeier D. Kolossa Thorsten Holz AAML 33 24 0 10 Feb 2021
Node-Level Membership Inference Attacks Against Graph Neural Networks Xinlei He Rui Wen Yixin Wu Michael Backes Yun Shen Yang Zhang 11 93 0 10 Feb 2021
Quantifying and Mitigating Privacy Risks of Contrastive Learning Xinlei He Yang Zhang 11 51 0 08 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 15 125 0 04 Feb 2021
Property Inference From Poisoning Melissa Chase Esha Ghosh Saeed Mahloujifar MIACV 19 77 0 26 Jan 2021
Membership Inference Attack on Graph Neural Networks Iyiola E. Olatunji Wolfgang Nejdl Megha Khosla AAML 38 97 0 17 Jan 2021
Towards a Robust and Trustworthy Machine Learning System Development: An Engineering Perspective Pulei Xiong Scott Buffett Shahrear Iqbal Philippe Lamontagne M. Mamun Heather Molyneaux OOD 34 15 0 08 Jan 2021
Practical Blind Membership Inference Attack via Differential Comparisons Bo Hui Yuchen Yang Haolin Yuan Philippe Burlina Neil Zhenqiang Gong Yinzhi Cao MIACV 30 119 0 05 Jan 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 75 100 0 04 Jan 2021
Robustness Threats of Differential Privacy Nurislam Tursynbek Aleksandr Petiushko Ivan V. Oseledets AAML 17 14 0 14 Dec 2020
When Machine Learning Meets Privacy: A Survey and Outlook B. Liu Ming Ding Sina shaham W. Rahayu F. Farokhi Zihuai Lin 10 281 0 24 Nov 2020
Monitoring-based Differential Privacy Mechanism Against Query-Flooding Parameter Duplication Attack Haonan Yan Xiaoguang Li Hui Li Jiamin Li Wenhai Sun Fenghua Li AAML 14 1 0 01 Nov 2020
Evaluation of Inference Attack Models for Deep Learning on Medical Data Maoqiang Wu Xinyue Zhang Jiahao Ding H. Nguyen Rong Yu M. Pan Stephen T. C. Wong MIACV 12 18 0 31 Oct 2020
Robust and Verifiable Information Embedding Attacks to Deep Neural Networks via Error-Correcting Codes Jinyuan Jia Binghui Wang Neil Zhenqiang Gong AAML 27 5 0 26 Oct 2020
Exploring the Security Boundary of Data Reconstruction via Neuron Exclusivity Analysis Xudong Pan Mi Zhang Yifan Yan Jiaming Zhu Zhemin Yang AAML 6 21 0 26 Oct 2020
CryptoGRU: Low Latency Privacy-Preserving Text Analysis With GRU Bo Feng Qian Lou Lei Jiang Geoffrey C. Fox 14 15 0 22 Oct 2020
Black-Box Ripper: Copying black-box models using generative evolutionary algorithms Antonio Bărbălău Adrian Cosma Radu Tudor Ionescu Marius Popescu MIACV MLAU 22 43 0 21 Oct 2020
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects Amir-Hossein Karimi Gilles Barthe Bernhard Schölkopf Isabel Valera FaML 14 172 0 08 Oct 2020
Don't Trigger Me! A Triggerless Backdoor Attack Against Deep Neural Networks A. Salem Michael Backes Yang Zhang 6 34 0 07 Oct 2020
Quantifying Privacy Leakage in Graph Embedding Vasisht Duddu A. Boutet Virat Shejwalkar MIACV 13 119 0 02 Oct 2020
ES Attack: Model Stealing against Deep Neural Networks without Data Hurdles Xiaoyong Yuan Lei Ding Lan Zhang Xiaolin Li D. Wu 15 40 0 21 Sep 2020
Local and Central Differential Privacy for Robustness and Privacy in Federated Learning Mohammad Naseri Jamie Hayes Emiliano De Cristofaro FedML 25 144 0 08 Sep 2020
Model extraction from counterfactual explanations Ulrich Aivodji Alexandre Bolot Sébastien Gambs MIACV MLAU 27 51 0 03 Sep 2020
Simulating Unknown Target Models for Query-Efficient Black-box Attacks Chen Ma L. Chen Junhai Yong MLAU OOD 41 17 0 02 Sep 2020
DeepPeep: Exploiting Design Ramifications to Decipher the Architecture of Compact DNNs N. Jha Sparsh Mittal Binod Kumar Govardhan Mattela AAML 13 12 0 30 Jul 2020
Label-Only Membership Inference Attacks Christopher A. Choquette-Choo Florian Tramèr Nicholas Carlini Nicolas Papernot MIACV MIALM 24 493 0 28 Jul 2020
A Survey of Privacy Attacks in Machine Learning M. Rigaki Sebastian Garcia PILM AAML 27 213 0 15 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 24 128 0 13 Jul 2020
Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain Ishai Rosenberg A. Shabtai Yuval Elovici L. Rokach AAML 26 12 0 05 Jul 2020
Generating Adversarial Examples with Controllable Non-transferability Renzhi Wang Tianwei Zhang Xiaofei Xie L. Ma Cong Tian Felix Juefei Xu Yang Liu SILM AAML 17 3 0 02 Jul 2020
Hermes Attack: Steal DNN Models with Lossless Inference Accuracy Yuankun Zhu Yueqiang Cheng Husheng Zhou Yantao Lu MIACV AAML 31 99 0 23 Jun 2020
SPEED: Secure, PrivatE, and Efficient Deep learning Arnaud Grivet Sébert Rafael Pinot Martin Zuber Cédric Gouy-Pailler Renaud Sirdey FedML 11 20 0 16 Jun 2020
Stealing Deep Reinforcement Learning Models for Fun and Profit Kangjie Chen Shangwei Guo Tianwei Zhang Xiaofei Xie Yang Liu MLAU MIACV OffRL 21 45 0 09 Jun 2020
Detecting and Understanding Real-World Differential Performance Bugs in Machine Learning Libraries Saeid Tizpaz-Niari Pavol Cerný Ashutosh Trivedi 6 24 0 03 Jun 2020
BadNL: Backdoor Attacks against NLP Models with Semantic-preserving Improvements Xiaoyi Chen A. Salem Dingfan Chen Michael Backes Shiqing Ma Qingni Shen Zhonghai Wu Yang Zhang SILM 24 224 0 01 Jun 2020
Revisiting Membership Inference Under Realistic Assumptions Bargav Jayaraman Lingxiao Wang Katherine Knipmeyer Quanquan Gu David E. Evans 11 147 0 21 May 2020
An Overview of Privacy in Machine Learning Emiliano De Cristofaro SILM 22 83 0 18 May 2020
Perturbing Inputs to Prevent Model Stealing J. Grana AAML SILM 13 5 0 12 May 2020
Defending Model Inversion and Membership Inference Attacks via Prediction Purification Ziqi Yang Bin Shao Bohan Xuan E. Chang Fan Zhang AAML 17 71 0 08 May 2020
MAZE: Data-Free Model Stealing Attack Using Zeroth-Order Gradient Estimation Sanjay Kariyappa A. Prakash Moinuddin K. Qureshi AAML 21 146 0 06 May 2020
When Machine Unlearning Jeopardizes Privacy Min Chen Zhikun Zhang Tianhao Wang Michael Backes Mathias Humbert Yang Zhang MIACV 23 216 0 05 May 2020
Enhancing network forensics with particle swarm and deep learning: The particle deep framework Nickolaos Koroniotis Nour Moustafa 6 34 0 02 May 2020
Privacy in Deep Learning: A Survey Fatemehsadat Mirshghallah Mohammadkazem Taram Praneeth Vepakomma Abhishek Singh Ramesh Raskar H. Esmaeilzadeh FedML 8 135 0 25 Apr 2020
ENSEI: Efficient Secure Inference via Frequency-Domain Homomorphic Convolution for Privacy-Preserving Visual Recognition S. Bian Tianchen Wang Masayuki Hiromoto Yiyu Shi Takashi Sato FedML 8 30 0 11 Mar 2020
Cryptanalytic Extraction of Neural Network Models Nicholas Carlini Matthew Jagielski Ilya Mironov FedML MLAU MIACV AAML 70 134 0 10 Mar 2020
Dynamic Backdoor Attacks Against Machine Learning Models A. Salem Rui Wen Michael Backes Shiqing Ma Yang Zhang AAML 16 269 0 07 Mar 2020
Stealing Black-Box Functionality Using The Deep Neural Tree Architecture Daniel Teitelman I. Naeh Shie Mannor 6 5 0 23 Feb 2020