NoPeek: Information leakage reduction to share activations in distributed deep learning

20 August 2020

Papers citing "NoPeek: Information leakage reduction to share activations in distributed deep learning"

22 / 22 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 46 0 0 14 Apr 2025
Theoretical Insights in Model Inversion Robustness and Conditional Entropy Maximization for Collaborative Inference Systems Song Xia Yi Yu Wenhan Yang Meiwen Ding Zhuo Chen Lingyu Duan Alex C. Kot Xudong Jiang 56 2 0 01 Mar 2025
Navigating the Designs of Privacy-Preserving Fine-tuning for Large Language Models Haonan Shi Tu Ouyang An Wang 31 0 0 08 Jan 2025
Privacy Protectability: An Information-theoretical Approach Siping Shi Bihai Zhang Dan Wang 23 1 0 25 May 2023
Model Extraction Attacks on Split Federated Learning Jingtao Li Adnan Siraj Rakin Xing Chen Li Yang Zhezhi He Deliang Fan C. Chakrabarti FedML 55 5 0 13 Mar 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 29 4 0 16 Feb 2023
Privacy and Efficiency of Communications in Federated Split Learning Zongshun Zhang Andrea Pinto Valeria Turina Flavio Esposito I. Matta FedML 19 32 0 04 Jan 2023
Scalable Collaborative Learning via Representation Sharing Frédéric Berdoz Abhishek Singh Martin Jaggi Ramesh Raskar FedML 19 3 0 20 Nov 2022
Combined Federated and Split Learning in Edge Computing for Ubiquitous Intelligence in Internet of Things: State of the Art and Future Directions Qiang Duan Shijing Hu Ruijun Deng Zhihui Lu FedML 23 61 0 20 Jul 2022
LSTMSPLIT: Effective SPLIT Learning based LSTM on Sequential Time-Series Data Lianlian Jiang Yuexuan Wang Wenyi Zheng Chao Jin Zengxiang Li Sin Gee Teo AI4TS 17 10 0 08 Mar 2022
Assessing Privacy Risks from Feature Vector Reconstruction Attacks Emily Wenger Francesca Falzon Josephine Passananti Haitao Zheng Ben Y. Zhao AAML 17 3 0 11 Feb 2022
Survey: Leakage and Privacy at Inference Time Marija Jegorova Chaitanya Kaul Charlie Mayor Alison Q. OÑeil Alexander Weir Roderick Murray-Smith Sotirios A. Tsaftaris PILM MIACV 17 71 0 04 Jul 2021
Advancements of federated learning towards privacy preservation: from federated learning to split learning Chandra Thapa Pathum Chamikara Mahawaga Arachchige S. Çamtepe FedML 11 82 0 25 Nov 2020
SplitEasy: A Practical Approach for Training ML models on Mobile Devices Kamalesh Palanisamy Vivek Khimani Moin Hussain Moti Dimitris Chatzopoulos 4 20 0 09 Nov 2020
The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems Sixu Hu Yuan N. Li Xu Liu Q. Li Zhaomin Wu Bingsheng He FedML 11 53 0 14 Jun 2020
On the Global Optima of Kernelized Adversarial Representation Learning Bashir Sadeghi Runyi Yu Vishnu Naresh Boddeti AAML 59 31 0 16 Oct 2019
A fast algorithm for computing distance correlation A. Chaudhuri Wenhao Hu 34 65 0 26 Oct 2018
Secure Face Matching Using Fully Homomorphic Encryption Vishnu Naresh Boddeti PICV CVBM 65 108 0 01 May 2018
Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning Julien Mairal 68 317 0 18 Feb 2014
The affinely invariant distance correlation J. Dueck Dominic Edelmann T. Gneiting Donald Richards 72 42 0 09 Oct 2012
Measuring and testing dependence by correlation of distances G. Székely Maria L. Rizzo N. K. Bakirov 175 2,577 0 28 Mar 2008