Enⅽrypteⅾ Traffiⅽ Anaⅼysis through Expⅼainabⅼe Ⅿaⅽhine Ⅼearning, M.Sc. Thesis Sharif University of Technology ; Jalili, Rasool (Supervisor)
Abstract
Impressive progress in hardwares and developing encryption algorithms in last two decades are caused increase in using encryption protocols in network communications. In last decade, users use privacy preserving networks like Jap and Tor to protect their privacy. These networks protect users' data from eavesdroppers by using three-layer encryption and intermediate nodes between user and target website. Recent researches show that Deep Neural Networks can predict websites viewed by users with high accuracy. In other words, privacy preserving networks suffer from information leakage. In this research, we introduced some of the most powerful methods in encrypted traffic classification and then...
Cataloging briefEnⅽrypteⅾ Traffiⅽ Anaⅼysis through Expⅼainabⅼe Ⅿaⅽhine Ⅼearning, M.Sc. Thesis Sharif University of Technology ; Jalili, Rasool (Supervisor)
Abstract
Impressive progress in hardwares and developing encryption algorithms in last two decades are caused increase in using encryption protocols in network communications. In last decade, users use privacy preserving networks like Jap and Tor to protect their privacy. These networks protect users' data from eavesdroppers by using three-layer encryption and intermediate nodes between user and target website. Recent researches show that Deep Neural Networks can predict websites viewed by users with high accuracy. In other words, privacy preserving networks suffer from information leakage. In this research, we introduced some of the most powerful methods in encrypted traffic classification and then...
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