Toward enhancing web privacy on HTTPS traffic: A novel SuperLearner attack model and an efficient defense approach with adversarial examples-Reference-Cited by-同舟云学术

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Toward enhancing web privacy on HTTPS traffic: A novel SuperLearner attack model and an efficient defense approach with adversarial examples

Published:2024-04 Issue: Volume:139 Page:103673
ISSN:0167-4048
Container-title:Computers & Security
language:en
Short-container-title:Computers & Security

Author:

Abolfathi Masoumeh^ORCID,Inturi Srivani,Banaei-Kashani Farnoush^ORCID,Jafarian J. Haadi^ORCID

Publisher

Elsevier BV

Subject

Law,General Computer Science

Reference55 articles.

1. A game-theoretically optimal defense paradigm against traffic analysis attacks using multipath routing and deception;Abolfathi,2022

2. DFD: adversarial learning-based approach to defend against website fingerprinting;Abusnaina,2020

3. Bimorphing: a bi-directional bursting defense against website fingerprinting attacks;Al-Naami;IEEE Trans. Dependable Secure Comput.,2019

4. Var-CNN: a data-efficient website fingerprinting attack based on deep learning;Bhat;Proc. Priv. Enh. Technol.,2019

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1. Secured osprey-based energy efficient routing and congestion control in WSN;Sustainable Computing: Informatics and Systems;2024-12

2. Innovative artificial intelligence and game theoretic approach for target tracking in the sensor network;Annals of Operations Research;2024-06-25

3. Optimized graph transformer with molecule attention network based multi class attack detection framework for enhancing privacy and security in WSN;Multimedia Tools and Applications;2024-06-15

4. Exploring the Synergy of Blockchain, IoT, and Edge Computing in Smart Traffic Management across Urban Landscapes;Journal of Grid Computing;2024-04-17

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