Unleashing the Tiger: Inference Attacks on Split Learning

4 December 2020

Papers citing "Unleashing the Tiger: Inference Attacks on Split Learning"

50 / 72 papers shown

Title
A Taxonomy of Attacks and Defenses in Split Learning Aqsa Shabbir Halil Ibrahim Kanpak Alptekin Küpçü Sinem Sav 41 0 0 09 May 2025
Quantifying Privacy Leakage in Split Inference via Fisher-Approximated Shannon Information Analysis Ruijun Deng Zhihui Lu Qiang Duan FedML 40 0 0 14 Apr 2025
Prompt Inference Attack on Distributed Large Language Model Inference Frameworks Xinjian Luo Ting Yu X. Xiao AAML SILM 83 1 0 12 Mar 2025
Split Adaptation for Pre-trained Vision Transformers Lixu Wang Bingqi Shang Y. Li Payal Mohapatra Wei Dong Xiao-Xu Wang Qi Zhu ViT 43 0 0 01 Mar 2025
Stealing Training Data from Large Language Models in Decentralized Training through Activation Inversion Attack Chenxi Dai Lin Lu Pan Zhou 42 0 0 22 Feb 2025
Efficient Split Learning LSTM Models for FPGA-based Edge IoT Devices Romina Soledad Molina Vukan Ninkovic D. Vukobratović Maria Liz Crespo Marco Zennaro 35 0 0 12 Feb 2025
SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Phillip Rieger Alessandro Pegoraro Kavita Kumari Tigist Abera Jonathan Knauer A. Sadeghi AAML 48 2 0 11 Jan 2025
Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Andrei Semenov Philip Zmushko Alexander Pichugin Aleksandr Beznosikov 86 0 0 16 Dec 2024
PrivTuner with Homomorphic Encryption and LoRA: A P3EFT Scheme for Privacy-Preserving Parameter-Efficient Fine-Tuning of AI Foundation Models Yang Li Wenhan Yu Jun Zhao 27 1 0 01 Oct 2024
Investigating Privacy Attacks in the Gray-Box Setting to Enhance Collaborative Learning Schemes Federico Mazzone Ahmad Al Badawi Y. Polyakov Maarten Everts Florian Hahn Andreas Peter MIACV AAML 31 0 0 25 Sep 2024
A Hybrid Quantum Neural Network for Split Learning Hevish Cowlessur Chandra Thapa T. Alpcan S. Çamtepe 27 0 0 25 Sep 2024
Enhancing Privacy in ControlNet and Stable Diffusion via Split Learning Dixi Yao 27 0 0 13 Sep 2024
$S^2$ NeRF: Privacy-preserving Training Framework for NeRF Bokang Zhang Yanglin Zhang Zhikun Zhang Jinglan Yang Lingying Huang Junfeng Wu 43 2 0 03 Sep 2024
Unveiling the Vulnerability of Private Fine-Tuning in Split-Based Frameworks for Large Language Models: A Bidirectionally Enhanced Attack Guanzhong Chen Zhenghan Qin Mingxin Yang Yajie Zhou Tao Fan Tianyu Du Zenglin Xu AAML 48 4 0 02 Sep 2024
CURE: Privacy-Preserving Split Learning Done Right Halil Ibrahim Kanpak Aqsa Shabbir Esra Genç Alptekin Küpçü Sinem Sav 24 0 0 12 Jul 2024
SplitLoRA: A Split Parameter-Efficient Fine-Tuning Framework for Large Language Models Zheng Lin Xuanjie Hu Yuxin Zhang Zhe Chen Zihan Fang Xianhao Chen Ang Li Praneeth Vepakomma Yue Gao 41 31 0 01 Jul 2024
Silver Linings in the Shadows: Harnessing Membership Inference for Machine Unlearning Nexhi Sula Abhinav Kumar Jie Hou Han Wang R. Tourani MU 23 0 0 01 Jul 2024
Inference Attacks: A Taxonomy, Survey, and Promising Directions Feng Wu Lei Cui Shaowen Yao Shui Yu 39 2 0 04 Jun 2024
LabObf: A Label Protection Scheme for Vertical Federated Learning Through Label Obfuscation Ying He Mingyang Niu Jingyu Hua Yunlong Mao Xu Huang Chen Li Sheng Zhong FedML 35 0 0 27 May 2024
A Stealthy Wrongdoer: Feature-Oriented Reconstruction Attack against Split Learning Xiaoyang Xu Mengda Yang Wenzhe Yi Ziang Li Juan Wang Hongxin Hu Yong Zhuang Yaxin Liu AAML 19 4 0 07 May 2024
Make Split, not Hijack: Preventing Feature-Space Hijacking Attacks in Split Learning Tanveer Khan Mindaugas Budzys A. Michalas 24 4 0 14 Apr 2024
AdaptSFL: Adaptive Split Federated Learning in Resource-constrained Edge Networks Zhengyi Lin Guanqiao Qu Wei Wei Xianhao Chen Kin K. Leung 46 48 0 19 Mar 2024
Wildest Dreams: Reproducible Research in Privacy-preserving Neural Network Training Tanveer Khan Mindaugas Budzys Khoa Nguyen A. Michalas 25 3 0 06 Mar 2024
Privacy-Preserving Collaborative Split Learning Framework for Smart Grid Load Forecasting Asif Iqbal P. Gope Biplab Sikdar 20 1 0 03 Mar 2024
A Survey of Privacy Threats and Defense in Vertical Federated Learning: From Model Life Cycle Perspective Lei Yu Meng Han Yiming Li Changting Lin Yao Zhang ... Yan Liu Haiqin Weng Yuseok Jeon Ka-Ho Chow Stacy Patterson FedML 58 9 0 06 Feb 2024
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance Wenqi Wei Ling Liu 23 16 0 02 Feb 2024
Unraveling Attacks in Machine Learning-based IoT Ecosystems: A Survey and the Open Libraries Behind Them Chao-Jung Liu Boxi Chen Wei Shao Chris Zhang Kelvin Wong Yi Zhang 19 3 0 22 Jan 2024
Secure Transformer Inference Protocol Mu Yuan Lan Zhang Xiang-Yang Li 30 3 0 14 Nov 2023
Edge-assisted U-Shaped Split Federated Learning with Privacy-preserving for Internet of Things Hengliang Tang Zihang Zhao Detian Liu Yang Cao Shiqiang Zhang Siqing You 13 1 0 08 Nov 2023
Weighted Sampled Split Learning (WSSL): Balancing Privacy, Robustness, and Fairness in Distributed Learning Environments Manish Osti Aashray Thakuri Basheer Qolomany Aos Mulahuwaish 13 0 0 27 Oct 2023
Passive Inference Attacks on Split Learning via Adversarial Regularization Xiaochen Zhu Xinjian Luo Yuncheng Wu Yangfan Jiang Xiaokui Xiao Beng Chin Ooi FedML 16 9 0 16 Oct 2023
Collaborative Distributed Machine Learning Sumit Kumar Jha Patrick Lincoln Sascha Rank A. Sunyaev 30 1 0 28 Sep 2023
Roulette: A Semantic Privacy-Preserving Device-Edge Collaborative Inference Framework for Deep Learning Classification Tasks Jingyi Li Guocheng Liao Lin Chen Xu Chen 19 8 0 06 Sep 2023
Split Without a Leak: Reducing Privacy Leakage in Split Learning Khoa Nguyen Tanveer Khan A. Michalas FedML 11 4 0 30 Aug 2023
Attesting Distributional Properties of Training Data for Machine Learning Vasisht Duddu Anudeep Das Nora Khayata Hossein Yalame T. Schneider Nirmal Asokan 40 5 0 18 Aug 2023
Defending Label Inference Attacks in Split Learning under Regression Setting Haoze Qiu Fei Zheng Chaochao Chen Xiaolin Zheng FedML AAML 21 2 0 18 Aug 2023
On the Trustworthiness Landscape of State-of-the-art Generative Models: A Survey and Outlook Mingyuan Fan Chengyu Wang Cen Chen Yang Liu Jun Huang HILM 31 3 0 31 Jul 2023
PATROL: Privacy-Oriented Pruning for Collaborative Inference Against Model Inversion Attacks Shiwei Ding Lan Zhang Miao Pan Xiaoyong Yuan AAML 19 5 0 20 Jul 2023
On the Robustness of Split Learning against Adversarial Attacks Mingyuan Fan Cen Chen Chengyu Wang Wenmeng Zhou Jun Huang AAML 15 8 0 16 Jul 2023
Analyzing the vulnerabilities in SplitFed Learning: Assessing the robustness against Data Poisoning Attacks Aysha Thahsin Zahir Ismail R. Shukla AAML FedML 27 6 0 04 Jul 2023
Evaluating Privacy Leakage in Split Learning Xinchi Qiu Ilias Leontiadis Luca Melis Alex Sablayrolles Pierre Stock 25 5 0 22 May 2023
Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information Kiwan Maeng Chuan Guo Sanjay Kariyappa G. E. Suh 11 8 0 06 May 2023
Vehicle as a Service (VaaS): Leverage Vehicles to Build Service Networks and Capabilities for Smart Cities Xianhao Chen Yiqin Deng Haichuan Ding Guanqiao Qu Haixia Zhang P. Li Yuguang Fang GNN 34 40 0 22 Apr 2023
Secure Split Learning against Property Inference, Data Reconstruction, and Feature Space Hijacking Attacks Yunlong Mao Zexi Xin Zhenyu Li Jue Hong Qingyou Yang Sheng Zhong MIACV AAML 18 10 0 19 Apr 2023
BadVFL: Backdoor Attacks in Vertical Federated Learning Mohammad Naseri Yufei Han Emiliano De Cristofaro FedML AAML 24 11 0 18 Apr 2023
On Feasibility of Server-side Backdoor Attacks on Split Learning Behrad Tajalli Oguzhan Ersoy S. Picek FedML SILM 45 8 0 19 Feb 2023
SplitOut: Out-of-the-Box Training-Hijacking Detection in Split Learning via Outlier Detection Ege Erdogan Unat Teksen Mehmet Salih Celiktenyildiz Alptekin Kupcu A. E. Cicek 27 4 0 16 Feb 2023
Threats, Vulnerabilities, and Controls of Machine Learning Based Systems: A Survey and Taxonomy Yusuke Kawamoto Kazumasa Miyake K. Konishi Y. Oiwa 16 4 0 18 Jan 2023
Security Analysis of SplitFed Learning M. A. Khan Virat Shejwalkar Amir Houmansadr Fatima M. Anwar FedML 8 11 0 04 Dec 2022
HashVFL: Defending Against Data Reconstruction Attacks in Vertical Federated Learning Pengyu Qiu Xuhong Zhang S. Ji Chong Fu Xing Yang Ting Wang FedML AAML 14 12 0 01 Dec 2022