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Quantifying Information Leakage from Gradients


May 28, 2021
Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh, Hamed Haddadi, Soteris Demetriou

* 18 pages, 9 figures 

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PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments


Apr 29, 2021
Fan Mo, Hamed Haddadi, Kleomenis Katevas, Eduard Marin, Diego Perino, Nicolas Kourtellis

* 15 pages, 8 figures, accepted to MobiSys 2021 

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Layer-wise Characterization of Latent Information Leakage in Federated Learning


Oct 17, 2020
Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh, Hamed Haddadi, Soteris Demetriou

* 17 pages, 11 figures 

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DarkneTZ: Towards Model Privacy at the Edge using Trusted Execution Environments


Apr 12, 2020
Fan Mo, Ali Shahin Shamsabadi, Kleomenis Katevas, Soteris Demetriou, Ilias Leontiadis, Andrea Cavallaro, Hamed Haddadi

* 13 pages, 8 figures, accepted to ACM MobiSys 2020 

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Towards Characterizing and Limiting Information Exposure in DNN Layers


Jul 13, 2019
Fan Mo, Ali Shahin Shamsabadi, Kleomenis Katevas, Andrea Cavallaro, Hamed Haddadi

* 5 pages, 6 figures, CCS PPML workshop 

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Weight-importance sparse training in keyword spotting


Jul 09, 2018
Sihao Xue, Zhenyi Ying, Fan Mo, Min Wang, Jue Sun


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