Ali Shahin Shamsabadi

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 51

Top Topics

Privacy Protection

Negative Training Examples

Top Venues

Proc. Priv. Enhancing Technol.

Publications

Ali Shahin Shamsabadi, Gefei Tan, Tudor Cebere, Aurélien Bellet, Hamed Haddadi, Nicolas Papernot, Xiao Wang, Adrian Weller
Confidential-DPproof: Confidential Proof of Differentially Private Training. ICLR (2024)
Franziska Boenisch, Adam Dziedzic, Roei Schuster, Ali Shahin Shamsabadi, Ilia Shumailov, Nicolas Papernot
When the Curious Abandon Honesty: Federated Learning Is Not Private. EuroS&P (2023)
Ali Shahin Shamsabadi, Brij Mohan Lal Srivastava, Aurélien Bellet, Nathalie Vauquier, Emmanuel Vincent, Mohamed Maouche, Marc Tommasi, Nicolas Papernot
Differentially Private Speaker Anonymization. Proc. Priv. Enhancing Technol. 2023 (1) (2023)
Adam Dziedzic, Christopher A. Choquette-Choo, Natalie Dullerud, Vinith M. Suriyakumar, Ali Shahin Shamsabadi, Muhammad Ahmad Kaleem, Somesh Jha, Nicolas Papernot, Xiao Wang
Private Multi-Winner Voting for Machine Learning. Proc. Priv. Enhancing Technol. 2023 (1) (2023)
Victoria Smith, Ali Shahin Shamsabadi, Carolyn Ashurst, Adrian Weller
Identifying and Mitigating Privacy Risks Stemming from Language Models: A Survey. CoRR (2023)
Ali Shahin Shamsabadi, Sierra Calanda Wyllie, Nicholas Franzese, Natalie Dullerud, Sébastien Gambs, Nicolas Papernot, Xiao Wang, Adrian Weller
Confidential-PROFITT: Confidential PROof of FaIr Training of Trees. ICLR (2023)
Sina Sajadmanesh, Ali Shahin Shamsabadi, Aurélien Bellet, Daniel Gatica-Perez
GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation. USENIX Security Symposium (2023)
Ali Shahin Shamsabadi, Jamie Hayes, Borja Balle, Adrian Weller
Mnemonist: Locating Model Parameters that Memorize Training Examples. UAI (2023)
Shimaa Ahmed, Yash Wani, Ali Shahin Shamsabadi, Mohammad Yaghini, Ilia Shumailov, Nicolas Papernot, Kassem Fawaz
Tubes Among Us: Analog Attack on Automatic Speaker Identification. USENIX Security Symposium (2023)
Franziska Boenisch, Adam Dziedzic, Roei Schuster, Ali Shahin Shamsabadi, Ilia Shumailov, Nicolas Papernot
Is Federated Learning a Practical PET Yet? CoRR (2023)
Ali Shahin Shamsabadi, Nicolas Papernot
Losing Less: A Loss for Differentially Private Deep Learning. Proc. Priv. Enhancing Technol. 2023 (3) (2023)
Franziska Boenisch, Adam Dziedzic, Roei Schuster, Ali Shahin Shamsabadi, Ilia Shumailov, Nicolas Papernot
Reconstructing Individual Data Points in Federated Learning Hardened with Differential Privacy and Secure Aggregation. EuroS&P (2023)
Chau Yi Li, Ricardo Sánchez-Matilla, Ali Shahin Shamsabadi, Riccardo Mazzon, Andrea Cavallaro
On the reversibility of adversarial attacks. CoRR (2022)
Shimaa Ahmed, Yash Wani, Ali Shahin Shamsabadi, Mohammad Yaghini, Ilia Shumailov, Nicolas Papernot, Kassem Fawaz
Pipe Overflow: Smashing Voice Authentication for Fun and Profit. CoRR (2022)
Ali Shahin Shamsabadi, Brij Mohan Lal Srivastava, Aurélien Bellet, Nathalie Vauquier, Emmanuel Vincent, Mohamed Maouche, Marc Tommasi, Nicolas Papernot
Differentially Private Speaker Anonymization. CoRR (2022)
Ali Shahin Shamsabadi, Mohammad Yaghini, Natalie Dullerud, Sierra Wyllie, Ulrich Aïvodji, Aisha Alaagib, Sébastien Gambs, Nicolas Papernot
Washing The Unwashable : On The (Im)possibility of Fairwashing Detection. NeurIPS (2022)
Sina Sajadmanesh, Ali Shahin Shamsabadi, Aurélien Bellet, Daniel Gatica-Perez
GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation. CoRR (2022)
Adam Dziedzic, Christopher A. Choquette-Choo, Natalie Dullerud, Vinith Menon Suriyakumar, Ali Shahin Shamsabadi, Muhammad Ahmad Kaleem, Somesh Jha, Nicolas Papernot, Xiao Wang
Private Multi-Winner Voting for Machine Learning. CoRR (2022)
Hengrui Jia, Hongyu Chen, Jonas Guan, Ali Shahin Shamsabadi, Nicolas Papernot
A Zest of LIME: Towards Architecture-Independent Model Distances. ICLR (2022)
Chau Yi Li, Ricardo Sánchez-Matilla, Ali Shahin Shamsabadi, Riccardo Mazzon, Andrea Cavallaro
On the Reversibility of Adversarial Attacks. ICIP (2021)
Ali Shahin Shamsabadi, Changjae Oh, Andrea Cavallaro
Semantically Adversarial Learnable Filters. IEEE Trans. Image Process. 30 (2021)
Franziska Boenisch, Adam Dziedzic, Roei Schuster, Ali Shahin Shamsabadi, Ilia Shumailov, Nicolas Papernot
When the Curious Abandon Honesty: Federated Learning Is Not Private. CoRR (2021)
Ali Shahin Shamsabadi, Francisco Sepúlveda Teixeira, Alberto Abad, Bhiksha Raj, Andrea Cavallaro, Isabel Trancoso
FoolHD: Fooling Speaker Identification by Highly Imperceptible Adversarial Disturbances. ICASSP (2021)
Ali Shahin Shamsabadi, Francisco Sepúlveda Teixeira, Alberto Abad, Bhiksha Raj, Andrea Cavallaro, Isabel Trancoso
FoolHD: Fooling speaker identification by Highly imperceptible adversarial Disturbances. CoRR (2020)
Ali Shahin Shamsabadi, Ricardo Sánchez-Matilla, Andrea Cavallaro
ColorFool: Semantic Adversarial Colorization. CVPR (2020)
Ali Shahin Shamsabadi, Changjae Oh, Andrea Cavallaro
Edgefool: an Adversarial Image Enhancement Filter. ICASSP (2020)
Ali Shahin Shamsabadi, Adrià Gascón, Hamed Haddadi, Andrea Cavallaro
PrivEdge: From Local to Distributed Private Training and Prediction. IEEE Trans. Inf. Forensics Secur. 15 (2020)
Ali Shahin Shamsabadi, Adrià Gascón, Hamed Haddadi, Andrea Cavallaro
PrivEdge: From Local to Distributed Private Training and Prediction. CoRR (2020)
Fan Mo, Ali Shahin Shamsabadi, Kleomenis Katevas, Soteris Demetriou, Ilias Leontiadis, Andrea Cavallaro, Hamed Haddadi
DarkneTZ: Towards Model Privacy at the Edge using Trusted Execution Environments. CoRR (2020)
Andrea Cavallaro, Mohammad Malekzadeh, Ali Shahin Shamsabadi
Deep Learning for Privacy in Multimedia. ACM Multimedia (2020)
Ricardo Sanchez-Matilla, Chau Yi Li, Ali Shahin Shamsabadi, Riccardo Mazzon, Andrea Cavallaro
Exploiting vulnerabilities of deep neural networks for privacy protection. CoRR (2020)
Ricardo Sanchez-Matilla, Chau Yi Li, Ali Shahin Shamsabadi, Riccardo Mazzon, Andrea Cavallaro
Exploiting Vulnerabilities of Deep Neural Networks for Privacy Protection. IEEE Trans. Multim. 22 (7) (2020)
Seyed Ali Osia, Ali Taheri, Ali Shahin Shamsabadi, Kleomenis Katevas, Hamed Haddadi, Hamid R. Rabiee
Deep Private-Feature Extraction. IEEE Trans. Knowl. Data Eng. 32 (1) (2020)
Fan Mo, Ali Shahin Shamsabadi, Kleomenis Katevas, Soteris Demetriou, Ilias Leontiadis, Andrea Cavallaro, Hamed Haddadi
DarkneTZ: towards model privacy at the edge using trusted execution environments. MobiSys (2020)
Ali Shahin Shamsabadi, Changjae Oh, Andrea Cavallaro
Semantically Adversarial Learnable Filters. CoRR (2020)
Seyed Ali Osia, Ali Shahin Shamsabadi, Sina Sajadmanesh, Ali Taheri, Kleomenis Katevas, Hamid R. Rabiee, Nicholas D. Lane, Hamed Haddadi
A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics. IEEE Internet Things J. 7 (5) (2020)
Fan Mo, Ali Shahin Shamsabadi, Kleomenis Katevas, Andrea Cavallaro, Hamed Haddadi
Poster: Towards Characterizing and Limiting Information Exposure in DNN Layers. CCS (2019)
Ali Shahin Shamsabadi, Changjae Oh, Andrea Cavallaro
EdgeFool: An Adversarial Image Enhancement Filter. CoRR (2019)
Chau Yi Li, Ali Shahin Shamsabadi, Ricardo Sanchez-Matilla, Riccardo Mazzon, Andrea Cavallaro
Scene Privacy Protection. ICASSP (2019)
Nitin Agrawal, Ali Shahin Shamsabadi, Matt J. Kusner, Adrià Gascón
QUOTIENT: Two-Party Secure Neural Network Training and Prediction. CCS (2019)
Fan Mo, Ali Shahin Shamsabadi, Kleomenis Katevas, Andrea Cavallaro, Hamed Haddadi
Towards Characterizing and Limiting Information Exposure in DNN Layers. CoRR (2019)
Nitin Agrawal, Ali Shahin Shamsabadi, Matt J. Kusner, Adrià Gascón
QUOTIENT: Two-Party Secure Neural Network Training and Prediction. CoRR (2019)
Ali Shahin Shamsabadi, Ricardo Sanchez-Matilla, Andrea Cavallaro
ColorFool: Semantic Adversarial Colorization. CoRR (2019)
Poonam Yadav, John Moore, Qi Li, Richard Mortier, Anthony Brown, Andy Crabtree, Chris Greenhalgh, Derek McAuley, Yousef Amar, Ali Shahin Shamsabadi, Hamed Haddadi
Providing Occupancy as a Service with Databox. CitiFog@SenSys (2018)
Ali Shahin Shamsabadi, Hamed Haddadi, Andrea Cavallaro
Distributed One-class Learning. CoRR (2018)
Seyed Ali Ossia, Ali Taheri, Ali Shahin Shamsabadi, Kleomenis Katevas, Hamed Haddadi, Hamid R. Rabiee
Deep Private-Feature Extraction. CoRR (2018)
Seyed Ali Ossia, Ali Shahin Shamsabadi, Ali Taheri, Hamid R. Rabiee, Hamed Haddadi
Private and Scalable Personal Data Analytics Using Hybrid Edge-to-Cloud Deep Learning. Computer 51 (5) (2018)
Ali Shahin Shamsabadi, Hamed Haddadi, Andrea Cavallaro
Distributed One-Class Learning. ICIP (2018)
Ali Shahin Shamsabadi, Massoud Babaie-Zadeh, Seyyede Zohreh Seyyedsalehi, Hamid R. Rabiee, Christian Jutten
A new algorithm for training sparse autoencoders. EUSIPCO (2017)
Seyed Ali Ossia, Ali Shahin Shamsabadi, Ali Taheri, Kleomenis Katevas, Hamid R. Rabiee, Nicholas D. Lane, Hamed Haddadi
Privacy-Preserving Deep Inference for Rich User Data on The Cloud. CoRR (2017)
Seyed Ali Ossia, Ali Shahin Shamsabadi, Ali Taheri, Hamid R. Rabiee, Nicholas D. Lane, Hamed Haddadi
A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics. CoRR (2017)