Ali Shahin Shamsabadi

According to our database, Ali Shahin Shamsabadi authored at least 35 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Losing Less: A Loss for Differentially Private Deep Learning.

Ali Shahin Shamsabadi, Nicolas Papernot

Proc. Priv. Enhancing Technol., July, 2023

Differentially Private Speaker Anonymization.

Ali Shahin Shamsabadi, Brij Mohan Lal Srivastava, Aurélien Bellet, Nathalie Vauquier, Emmanuel Vincent, Mohamed Maouche, Marc Tommasi, Nicolas Papernot

Proc. Priv. Enhancing Technol., January, 2023

Private Multi-Winner Voting for Machine Learning.

Adam Dziedzic, Christopher A. Choquette-Choo, Natalie Dullerud, Vinith M. Suriyakumar, Ali Shahin Shamsabadi, Muhammad Ahmad Kaleem, Somesh Jha, Nicolas Papernot, Xiao Wang

Proc. Priv. Enhancing Technol., January, 2023

Identifying and Mitigating Privacy Risks Stemming from Language Models: A Survey.

Victoria Smith, Ali Shahin Shamsabadi, Carolyn Ashurst, Adrian Weller

CoRR, 2023

Is Federated Learning a Practical PET Yet?

Franziska Boenisch, Adam Dziedzic, Roei Schuster, Ali Shahin Shamsabadi, Ilia Shumailov, Nicolas Papernot

CoRR, 2023

GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation.

Sina Sajadmanesh, Ali Shahin Shamsabadi, Aurélien Bellet, Daniel Gatica-Perez

Proceedings of the 32nd USENIX Security Symposium, 2023

Tubes Among Us: Analog Attack on Automatic Speaker Identification.

Shimaa Ahmed, Yash Wani, Ali Shahin Shamsabadi, Mohammad Yaghini, Ilia Shumailov, Nicolas Papernot, Kassem Fawaz

Proceedings of the 32nd USENIX Security Symposium, 2023

Mnemonist: Locating Model Parameters that Memorize Training Examples.

Ali Shahin Shamsabadi, Jamie Hayes, Borja Balle, Adrian Weller

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Confidential-PROFITT: Confidential PROof of FaIr Training of Trees.

Ali Shahin Shamsabadi, Sierra Calanda Wyllie, Nicholas Franzese, Natalie Dullerud, Sébastien Gambs, Nicolas Papernot, Xiao Wang, Adrian Weller

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Reconstructing Individual Data Points in Federated Learning Hardened with Differential Privacy and Secure Aggregation.

Franziska Boenisch, Adam Dziedzic, Roei Schuster, Ali Shahin Shamsabadi, Ilia Shumailov, Nicolas Papernot

Proceedings of the 8th IEEE European Symposium on Security and Privacy, 2023

When the Curious Abandon Honesty: Federated Learning Is Not Private.

Franziska Boenisch, Adam Dziedzic, Roei Schuster, Ali Shahin Shamsabadi, Ilia Shumailov, Nicolas Papernot

Proceedings of the 8th IEEE European Symposium on Security and Privacy, 2023

2022

Pipe Overflow: Smashing Voice Authentication for Fun and Profit.

Shimaa Ahmed, Yash Wani, Ali Shahin Shamsabadi, Mohammad Yaghini, Ilia Shumailov, Nicolas Papernot, Kassem Fawaz

CoRR, 2022

Washing The Unwashable : On The (Im)possibility of Fairwashing Detection.

Ali Shahin Shamsabadi, Mohammad Yaghini, Natalie Dullerud, Sierra Calanda Wyllie, Ulrich Aïvodji, Aisha Alaagib, Sébastien Gambs, Nicolas Papernot

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Zest of LIME: Towards Architecture-Independent Model Distances.

Hengrui Jia, Hongyu Chen, Jonas Guan, Ali Shahin Shamsabadi, Nicolas Papernot

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Semantically Adversarial Learnable Filters.

Ali Shahin Shamsabadi, Changjae Oh, Andrea Cavallaro

IEEE Trans. Image Process., 2021

On the Reversibility of Adversarial Attacks.

Chau Yi Li, Ricardo Sánchez-Matilla, Ali Shahin Shamsabadi, Riccardo Mazzon, Andrea Cavallaro

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

FoolHD: Fooling Speaker Identification by Highly Imperceptible Adversarial Disturbances.

Ali Shahin Shamsabadi, Francisco Sepúlveda Teixeira, Alberto Abad, Bhiksha Raj, Andrea Cavallaro, Isabel Trancoso

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

Exploiting Vulnerabilities of Deep Neural Networks for Privacy Protection.

Ricardo Sanchez-Matilla, Chau Yi Li, Ali Shahin Shamsabadi, Riccardo Mazzon, Andrea Cavallaro

IEEE Trans. Multim., 2020

Deep Private-Feature Extraction.

Seyed Ali Osia, Ali Taheri, Ali Shahin Shamsabadi, Kleomenis Katevas, Hamed Haddadi, Hamid R. Rabiee

IEEE Trans. Knowl. Data Eng., 2020

PrivEdge: From Local to Distributed Private Training and Prediction.

Ali Shahin Shamsabadi, Adrià Gascón, Hamed Haddadi, Andrea Cavallaro

IEEE Trans. Inf. Forensics Secur., 2020

A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics.

Seyed Ali Osia, Ali Shahin Shamsabadi, Sina Sajadmanesh, Ali Taheri, Kleomenis Katevas, Hamid R. Rabiee, Nicholas D. Lane, Hamed Haddadi

IEEE Internet Things J., 2020

DarkneTZ: towards model privacy at the edge using trusted execution environments.

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

Proceedings of the MobiSys '20: The 18th Annual International Conference on Mobile Systems, 2020

Deep Learning for Privacy in Multimedia.

Andrea Cavallaro, Mohammad Malekzadeh, Ali Shahin Shamsabadi

Proceedings of the MM '20: The 28th ACM International Conference on Multimedia, 2020

Edgefool: an Adversarial Image Enhancement Filter.

Ali Shahin Shamsabadi, Changjae Oh, Andrea Cavallaro

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

ColorFool: Semantic Adversarial Colorization.

Ali Shahin Shamsabadi, Ricardo Sánchez-Matilla, Andrea Cavallaro

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Towards Characterizing and Limiting Information Exposure in DNN Layers.

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

CoRR, 2019

Scene Privacy Protection.

Chau Yi Li, Ali Shahin Shamsabadi, Ricardo Sanchez-Matilla, Riccardo Mazzon, Andrea Cavallaro

Proceedings of the IEEE International Conference on Acoustics, 2019

Poster: Towards Characterizing and Limiting Information Exposure in DNN Layers.

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

Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, 2019

QUOTIENT: Two-Party Secure Neural Network Training and Prediction.

Nitin Agrawal, Ali Shahin Shamsabadi, Matt J. Kusner, Adrià Gascón

Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, 2019

2018

Private and Scalable Personal Data Analytics Using Hybrid Edge-to-Cloud Deep Learning.

Seyed Ali Ossia, Ali Shahin Shamsabadi, Ali Taheri, Hamid R. Rabiee, Hamed Haddadi

Computer, 2018

Providing Occupancy as a Service with Databox.

Poonam Yadav, John Moore, Qi Li, Richard Mortier, Anthony Brown, Andy Crabtree, Chris Greenhalgh, Derek McAuley, Yousef Amar, Ali Shahin Shamsabadi, Hamed Haddadi

Proceedings of the 1st ACM International Workshop on Smart Cities and Fog Computing, 2018

Distributed One-Class Learning.

Ali Shahin Shamsabadi, Hamed Haddadi, Andrea Cavallaro

Proceedings of the 2018 IEEE International Conference on Image Processing, 2018

2017

Privacy-Preserving Deep Inference for Rich User Data on The Cloud.

Seyed Ali Ossia, Ali Shahin Shamsabadi, Ali Taheri, Kleomenis Katevas, Hamid R. Rabiee, Nicholas D. Lane, Hamed Haddadi

CoRR, 2017

A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics.

Seyed Ali Ossia, Ali Shahin Shamsabadi, Ali Taheri, Hamid R. Rabiee, Nicholas D. Lane, Hamed Haddadi

CoRR, 2017

A new algorithm for training sparse autoencoders.

Ali Shahin Shamsabadi, Massoud Babaie-Zadeh, Seyyede Zohreh Seyyedsalehi, Hamid R. Rabiee, Christian Jutten

Proceedings of the 25th European Signal Processing Conference, 2017