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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01g732dd06b
Title: Internet Measurement for the Prevention and Detection of Internet Surveillance
Authors: Roberts, Laura M
Advisors: Felten, Edward W
Contributors: Computer Science Department
Keywords: DNS
IPv6
Measurement
Networks
Security
Tor
Subjects: Computer science
Issue Date: 2020
Publisher: Princeton, NJ : Princeton University
Abstract: Surveillance is a tactic of societal control: Observation of people’s behavior allows the observer to manipulate and steer people’s future behavior in a way that serves the observer’s interests. With new technologies come new, easier ways of surveilling people. This dissertation concerns itself with Internet technologies in particular and presents how Internet measurement can be used to prevent and detect Internet surveillance. “Internet surveillance” is the observation of people’s online activities. “Internet measurement” comprises technical means of measuring interesting characteristics of the Internet (e.g. packet round-trip time, protocol usage, etc.) in order to gain better understanding of the Internet and improve its performance, security, etc. So in other words, this dissertation presents how various Internet measurement techniques can be used for preventing and detecting the observation of people’s online activities. In order to achieve the goal of preventing surveillance, we use Internet measurement techniques to strengthen the Tor anonymity network (a system that seeks to thwart Internet surveillance and censorship) by exposing vulnerabilities and suggesting possible solutions. In order to achieve the goal of detecting surveillance, we develop a proof of concept system that uses Internet measurement techniques to catch surveillants.
URI: http://arks.princeton.edu/ark:/88435/dsp01g732dd06b
Alternate format: The Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog: catalog.princeton.edu
Type of Material: Academic dissertations (Ph.D.)
Language: en
Appears in Collections:Computer Science

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