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1
Intro
2
Motivation
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The Scenario
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Brief Partial Overview of SSL/TLS
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How Can "I Know What You Saw"? 1. How are YouTube videos encoded?
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Introduction To HTTP Adaptive Streaming (HAS)
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YouTube Encrypted Network Traffic
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YouTube Flow Patterns - The Web Proxy Perspective
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YouTube HTTP Byte Range
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Related Works
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Proposed Machine Learning Solution 1. Traffic Analysis
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BPP Index Vs Download Copy
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Pre-Processing
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Proposed algorithms 1. Support Vector Machines (SVM) with Radial Basis Function (RBF) . With a BPP feature vector
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SVM with Radial Basis Function (RBF) Kernel
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BPP Set Feature
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NN Algorithm • Similarity score between two BPP-sets is the cardinality of the intersection set
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Classification Accuracy
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Confusion Matrices
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Ongoing Results
Description:
Explore a 28-minute Black Hat conference talk that delves into the security implications of HTTP Adaptive Streaming (HAS) and Dynamic Adaptive Streaming over HTTP (DASH) for online video consumption. Discover how Ran Dubin investigates the potential for identifying viewed content through traffic analysis, focusing on YouTube's implementation in the Chrome browser. Learn about the encoding of YouTube videos, encrypted network traffic patterns, and proposed machine learning solutions using Support Vector Machines (SVM) and Neural Networks (NN) for classification. Gain insights into the accuracy of these methods and their potential impact on user privacy in the age of widespread mobile video streaming.

I Know What You Saw Last Minute - The Chrome Browser Case

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#Conference Talks #Black Hat #Information Security (InfoSec) #Cybersecurity #Computer Science #Machine Learning #Network Security #Network Traffic Analysis
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Intro