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Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning

1 April 2018

Battista Biggio

Papers citing "Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning"

50 / 318 papers shown

Title
AI Maintenance: A Robustness Perspective Pin-Yu Chen Payel Das 86 14 0 08 Jan 2023
Sublinear Time Algorithms for Several Geometric Optimization (With Outliers) Problems In Machine Learning Hu Ding 155 0 0 07 Jan 2023
Distributed Machine Learning for UAV Swarms: Computing, Sensing, and Semantics Yahao Ding Zhaohui Yang Quoc-Viet Pham Zhaoyang Zhang M. Shikh-Bahaei 86 38 0 03 Jan 2023
XMAM:X-raying Models with A Matrix to Reveal Backdoor Attacks for Federated Learning Jianyi Zhang Fangjiao Zhang Qichao Jin Zhiqiang Wang Xiaodong Lin X. Hei AAML FedML 92 1 0 28 Dec 2022
FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data Minghong Fang Jia-Wei Liu Michinari Momma Yi Sun 76 4 0 13 Dec 2022
Selective Amnesia: On Efficient, High-Fidelity and Blind Suppression of Backdoor Effects in Trojaned Machine Learning Models Rui Zhu Di Tang Siyuan Tang Wenyuan Xu Haixu Tang AAML FedML 101 14 0 09 Dec 2022
Vicious Classifiers: Data Reconstruction Attack at Inference Time Mohammad Malekzadeh Deniz Gunduz AAML MIACV 66 0 0 08 Dec 2022
Hijack Vertical Federated Learning Models As One Party Pengyu Qiu Xuhong Zhang Shouling Ji Changjiang Li Yuwen Pu Xing Yang Ting Wang FedML 124 6 0 01 Dec 2022
Adversarial Attacks are a Surprisingly Strong Baseline for Poisoning Few-Shot Meta-Learners E. T. Oldewage J. Bronskill Richard Turner 68 3 0 23 Nov 2022
Analysis and Detectability of Offline Data Poisoning Attacks on Linear Dynamical Systems Alessio Russo AAML 40 3 0 16 Nov 2022
M-to-N Backdoor Paradigm: A Multi-Trigger and Multi-Target Attack to Deep Learning Models Linshan Hou Zhongyun Hua Yuhong Li Yifeng Zheng Leo Yu Zhang AAML 109 3 0 03 Nov 2022
Amplifying Membership Exposure via Data Poisoning Yufei Chen Chao Shen Yun Shen Cong Wang Yang Zhang AAML 125 33 0 01 Nov 2022
New data poison attacks on machine learning classifiers for mobile exfiltration M. A. Ramírez Sangyoung Yoon Ernesto Damiani H. A. Hamadi C. Ardagna Nicola Bena Young-Ji Byon Tae-Yeon Kim C. Cho C. Yeun AAML 83 4 0 20 Oct 2022
A.I. Robustness: a Human-Centered Perspective on Technological Challenges and Opportunities Andrea Tocchetti Lorenzo Corti Agathe Balayn Mireia Yurrita Philip Lippmann Marco Brambilla Jie Yang 87 14 0 17 Oct 2022
Data Poisoning Attacks Against Multimodal Encoders Ziqing Yang Xinlei He Zheng Li Michael Backes Mathias Humbert Pascal Berrang Yang Zhang AAML 179 52 0 30 Sep 2022
GAGA: Deciphering Age-path of Generalized Self-paced Regularizer Xingyu Qu Diyang Li Xiaohan Zhao Bin Gu 81 1 0 15 Sep 2022
Federated Learning based on Defending Against Data Poisoning Attacks in IoT Jiayin Li Wenzhong Guo Xingshuo Han Jianping Cai Ximeng Liu AAML 127 1 0 14 Sep 2022
Defend Data Poisoning Attacks on Voice Authentication Ke Li Cameron Baird D. Lin AAML 86 9 0 09 Sep 2022
Reducing Certified Regression to Certified Classification for General Poisoning Attacks Zayd Hammoudeh Daniel Lowd AAML 82 10 0 29 Aug 2022
SNAP: Efficient Extraction of Private Properties with Poisoning Harsh Chaudhari John Abascal Alina Oprea Matthew Jagielski Florian Tramèr Jonathan R. Ullman MIACV 111 33 0 25 Aug 2022
Auditing Membership Leakages of Multi-Exit Networks Zheng Li Yiyong Liu Xinlei He Ning Yu Michael Backes Yang Zhang AAML 73 34 0 23 Aug 2022
An Input-Aware Mimic Defense Theory and its Practice Jiale Fu Yali Yuan Jiajun He Sichu Liang Zhe Huang Hongyu Zhu AAML 67 0 0 22 Aug 2022
Training-Time Attacks against k-Nearest Neighbors Ara Vartanian Will Rosenbaum Scott Alfeld 53 1 0 15 Aug 2022
Testing the Robustness of Learned Index Structures Matthias Bachfischer Renata Borovica-Gajic Benjamin I. P. Rubinstein AAML 49 1 0 23 Jul 2022
Careful What You Wish For: on the Extraction of Adversarially Trained Models Kacem Khaled Gabriela Nicolescu F. Magalhães MIACV AAML 78 4 0 21 Jul 2022
Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications Ali Raza Shujun Li K. Tran L. Koehl Kim Duc Tran AAML 155 4 0 18 Jul 2022
Enhanced Security and Privacy via Fragmented Federated Learning N. Jebreel J. Domingo-Ferrer Alberto Blanco-Justicia David Sánchez FedML 91 28 0 13 Jul 2022
A law of adversarial risk, interpolation, and label noise Daniel Paleka Amartya Sanyal NoLa AAML 113 10 0 08 Jul 2022
Federated and Transfer Learning: A Survey on Adversaries and Defense Mechanisms Ehsan Hallaji R. Razavi-Far M. Saif AAML FedML 79 13 0 05 Jul 2022
Defending against the Label-flipping Attack in Federated Learning N. Jebreel J. Domingo-Ferrer David Sánchez Alberto Blanco-Justicia AAML 73 37 0 05 Jul 2022
FL-Defender: Combating Targeted Attacks in Federated Learning N. Jebreel J. Domingo-Ferrer AAML FedML 105 61 0 02 Jul 2022
Threat Assessment in Machine Learning based Systems L. Tidjon Foutse Khomh 61 17 0 30 Jun 2022
Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experiments Jinkun Lin Anqi Zhang Mathias Lécuyer Jinyang Li Aurojit Panda S. Sen TDI FedML 79 55 0 20 Jun 2022
Edge Security: Challenges and Issues Xin Jin Charalampos Katsis Fan Sang Jiahao Sun A. Kundu Ramana Rao Kompella 95 9 0 14 Jun 2022
Certifying Data-Bias Robustness in Linear Regression Anna P. Meyer Aws Albarghouthi Loris Dántoni 65 3 0 07 Jun 2022
Circumventing Backdoor Defenses That Are Based on Latent Separability Xiangyu Qi Tinghao Xie Yiming Li Saeed Mahloujifar Prateek Mittal AAML 131 11 0 26 May 2022
Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free Tianlong Chen Zhenyu Zhang Yihua Zhang Shiyu Chang Sijia Liu Zhangyang Wang AAML 80 25 0 24 May 2022
SafeNet: The Unreasonable Effectiveness of Ensembles in Private Collaborative Learning Harsh Chaudhari Matthew Jagielski Alina Oprea 85 7 0 20 May 2022
Autonomy and Intelligence in the Computing Continuum: Challenges, Enablers, and Future Directions for Orchestration Henna Kokkonen Lauri Lovén Naser Hossein Motlagh Abhishek Kumar Juha Partala ... M. Bennis Sasu Tarkoma Schahram Dustdar Susanna Pirttikangas J. Riekki 107 27 0 03 May 2022
Backdooring Explainable Machine Learning Maximilian Noppel Lukas Peter Christian Wressnegger AAML 79 5 0 20 Apr 2022
Adversarial Analysis of the Differentially-Private Federated Learning in Cyber-Physical Critical Infrastructures Md Tamjid Hossain S. Badsha Hung M. La Haoting Shen Shafkat Islam Ibrahim Khalil X. Yi AAML 65 3 0 06 Apr 2022
Breaking the De-Pois Poisoning Defense Alaa Anani M. C. Ghanem L. A. Khaliq AAML 55 0 0 03 Apr 2022
Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets Florian Tramèr Reza Shokri Ayrton San Joaquin Hoang Minh Le Matthew Jagielski Sanghyun Hong Nicholas Carlini MIACV 141 123 0 31 Mar 2022
Robust Unlearnable Examples: Protecting Data Against Adversarial Learning Shaopeng Fu Fengxiang He Yang Liu Li Shen Dacheng Tao 80 26 0 28 Mar 2022
WaveFuzz: A Clean-Label Poisoning Attack to Protect Your Voice Yunjie Ge Qianqian Wang Jingfeng Zhang Juntao Zhou Yunzhu Zhang Chao Shen AAML 98 6 0 25 Mar 2022
A Tutorial on Adversarial Learning Attacks and Countermeasures Cato Pauling Michael Gimson Muhammed Qaid Ahmad Kida Basel Halak AAML 94 11 0 21 Feb 2022
Poisoning Attacks and Defenses on Artificial Intelligence: A Survey M. A. Ramírez Song-Kyoo Kim H. A. Hamadi Ernesto Damiani Young-Ji Byon Tae-Yeon Kim C. Cho C. Yeun AAML 94 37 0 21 Feb 2022
Trusted AI in Multi-agent Systems: An Overview of Privacy and Security for Distributed Learning Chuan Ma Jun Li Kang Wei Bo Liu Ming Ding Long Yuan Zhu Han H. Vincent Poor 106 48 0 18 Feb 2022
Holistic Adversarial Robustness of Deep Learning Models Pin-Yu Chen Sijia Liu AAML 105 16 0 15 Feb 2022
AnoMili: Spoofing Prevention and Explainable Anomaly Detection for the 1553 Military Avionic Bus Efrat Levy Nadav Maman A. Shabtai Yuval Elovici 47 15 0 14 Feb 2022