1.6k citations · 2.1k across the 35 of their papers we have counts for
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Improving Deep Learning with Differential Privacy using Gradient Encoding and Denoising
Milad Nasr, Reza Shokri, Amir houmansadr
Deep learning models leak significant amounts of information about their training datasets. Previous work has investigated training models with differential privacy (DP) guarantees…
Asymptotic Privacy Loss due to Time Series Matching of Dependent Users
Nazanin Takbiri, Minting Chen, Dennis L. Goeckel +2
The Internet of Things (IoT) promises to improve user utility by tuning applications to user behavior, but revealing the characteristics of a user's behavior presents a significant…
Practical Traffic Analysis Attacks on Secure Messaging Applications
Alireza Bahramali, Ramin Soltani, Amir Houmansadr +2
Instant Messaging (IM) applications like Telegram, Signal, and WhatsApp have become extremely popular in recent years. Unfortunately, such IM services have been targets of continuo…
Blind Adversarial Network Perturbations
Milad Nasr, Alireza Bahramali, Amir Houmansadr
Deep Neural Networks (DNNs) are commonly used for various traffic analysis problems, such as website fingerprinting and flow correlation, as they outperform traditional (e.g., stat…