OVERCOMING TOR: AN ANALYSIS OF VIDEO FINGERPRINTING ATTACKS WITH MACHINE LEARNING
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Authors
Thomas, Trevor J.
Subjects
video fingerprinting
AI
TOR
artificial intelligence
The Onion Router
AI
TOR
artificial intelligence
The Onion Router
Advisors
Barton, Armon C.
Date of Issue
2023-09
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
Terrorist groups and violent extremist organizations have taken advantage of the anonymity provided by The Onion Router (Tor). They use it to clandestinely distribute video media to recruit and spread propaganda as well as incite others to commit acts of terrorism. This thesis seeks to continue a line of work in developing machine learning algorithms to conduct video fingerprinting attacks on network traffic transmitted over Tor in a closed world environment. It will expand upon previous research by using multiple media platforms for videos being streamed. The end goal from this line of research is a future product that the Department of Defense can apply against real world network traffic to identify individuals using Tor and the dark web for recruiting, training, and incitement of terror as well as identify individuals that are actively being recruited.
Type
Thesis
Description
Series/Report No
Department
Computer Science (CS)
Organization
Identifiers
NPS Report Number
Sponsors
Funder
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Citation
Distribution Statement
Approved for public release. Distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.