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Mockingbird: Defending Against Deep-Learning-Based Website Fingerprinting Attacks with Adversarial Traces
- Mohammad Saidur Rahman
- Mohsen Imani
- Nate Mathews
- Matthew Wright
Date created: 2024-06-13 05:34 PM | Last Updated: 2024-06-25 04:00 PM
Category: Project
Description: This repository contains data of the paper Mockingbird: Defending Against Deep-Learning-Based Website Fingerprinting Attacks with Adversarial Traces, published in IEEE Transactions on Information Forensics and Security (TIFS). Mockingbird is designed to work against deep-learning-based website fingerprinting attacks. Extensive evaluation shows that Mockingbird is effective against both white-box and black-box attacks including a more advanced intersection attacks.
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