Ali Shahin Shamsabadi
Ali Shahin Shamsabadi
Research Associate at The Alan Turing Institute, Visitor at Vector Institute
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A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics
SA Osia, AS Shamsabadi, A Taheri, HR Rabiee, N Lane, H Haddadi
IEEE Internet of Things Journal, 2020
QUOTIENT: Two-Party Secure Neural Network Training and Prediction
N Agrawal, AS Shamsabadi, MJ Kusner, A Gascón
26th ACM Conference on Computer and Communications Security (CCS), 2019, 2019
DarkneTZ: Towards Model Privacy at the Edge using Trusted Execution Environments
F Mo, AS Shamsabadi, K Katevas, S Demetriou, I Leontiadis, A Cavallaro, ...
ACM International Conference on Mobile Systems, Applications, and Services …, 2020
ColorFool: Semantic Adversarial Colorization
AS Shamsabadi, R Sanchez-Matilla, A Cavallaro
Conference on Computer Vision and Pattern Recognition (CVPR), 2020
Deep Private-Feature Extraction
SA Osia, A Taheri, AS Shamsabadi, K Katevas, H Haddadi, HR Rabiee
IEEE Transactions on Knowledge and Data Engineering, 2018
Private and scalable personal data analytics using hybrid edge-to-cloud deep learning
SA Osia, AS Shamsabadi, A Taheri, HR Rabiee, H Haddadi
Computer 51 (5), 42-49, 2018
Scene privacy protection
CY Li, AS Shamsabadi, R Sanchez-Matilla, R Mazzon, A Cavallaro
44th IEEE International Conference on Acoustics, Speech and Signal …, 2019
Exploiting vulnerabilities of deep neural networks for privacy protection
R Sanchez-Matilla, CY Li, AS Shamsabadi, R Mazzon, A Cavallaro
IEEE Transactions on Multimedia 22 (7), 1862-1873, 2020
FoolHD: Fooling speaker identification by Highly imperceptible adversarial Disturbances
AS Shamsabadi, FS Teixeira, A Abad, B Raj, A Cavallaro, I Trancoso
46th IEEE International Conference on Acoustics, Speech, and Signal …, 2021
EdgeFool: An Adversarial Image Enhancement Filter
AS Shamsabadi, C Oh, A Cavallaro
45th IEEE International Conference on Acoustics, Speech, and Signal …, 2020
When the curious abandon honesty: Federated learning is not private
F Boenisch, A Dziedzic, R Schuster, AS Shamsabadi, I Shumailov, ...
arXiv preprint arXiv:2112.02918, 2021
PrivEdge: From Local to Distributed Private Training and Prediction
AS Shamsabadi, A Gascon, H Haddadi, A Cavallaro
IEEE Transactions on Information Forensics and Security (TIFS), 2020
Privacy-preserving deep inference for rich user data on the cloud
SA Osia, AS Shamsabadi, A Taheri, K Katevas, HR Rabiee, ND Lane, ...
arXiv preprint arXiv:1710.01727, 2017
Distributed One-class Learning
AS Shamsabadi, H Haddadi, A Cavallaro
25th IEEE International Conference on Image Processing (ICIP), 2018, 4123-4127, 2018
A new algorithm for training sparse autoencoders
AS Shamsabadi, M Babaie-Zadeh, SZ Seyyedsalehi, HR Rabiee, ...
25th European Signal Processing Conference (EUSIPCO), 2141-2145, 2017
GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation
S Sajadmanesh, AS Shamsabadi, A Bellet, D Gatica-Perez
arXiv preprint arXiv:2203.00949, 2022
Semantically adversarial learnable filters
AS Shamsabadi, C Oh, A Cavallaro
IEEE Transactions on Image Processing 30, 8075-8087, 2021
Towards characterizing and limiting information exposure in DNN layers
F Mo, AS Shamsabadi, K Katevas, A Cavallaro, H Haddadi
arXiv preprint arXiv:1907.06034, 2019
Differentially private speaker anonymization
AS Shamsabadi, BML Srivastava, A Bellet, N Vauquier, E Vincent, ...
arXiv preprint arXiv:2202.11823, 2022
Deep learning for privacy in multimedia
A Cavallaro, M Malekzadeh, AS Shamsabadi
Proceedings of the 28th ACM International Conference on Multimedia, 4777-4778, 2020
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