Troll Patrol: Detecting Blocked Tor Bridges

dc.contributor.advisorGoldberg, Ian
dc.contributor.authorVecna, Ivy
dc.date.accessioned2024-09-16T20:11:15Z
dc.date.available2024-09-16T20:11:15Z
dc.date.issued2024-09-16
dc.date.submitted2024-09-06
dc.description.abstractTor is an important tool for protecting people against Internet surveillance and censorship. Therefore, some governments that wish to monitor or restrict their people’s use of the Internet attempt to block access to Tor. Bridges are circumvention proxies that provide routes around this censorship, enabling people to access Tor, even in countries that ordinarily censor it. However, a motivated censor may work to identify these bridges and block access to them. To impede the censor’s attempts at identifying and blocking bridges, reputation-based systems for bridge distribution such as Hyphae, Salmon, and Lox have been proposed. These systems place greater trust in users when the bridges they know remain uncensored and reduced trust in users when bridges they know become censored. In order to enact these changes in trust, it is necessary to know which bridges have been blocked and which have not, but Tor does not currently have a systematic way to detect blocked bridges. In this work, we present Troll Patrol, a system for automatically detecting censorship of Tor bridges. This system infers bridge reachability based on already-existing bridge usage statistics and novel anonymous user reports that we design for this purpose. We evaluate our system using a simulation and demonstrate that user reports improve our ability to detect bridge censorship, compared to using statistics on bridge use alone. We describe an attack that allows the censor to evade detection if classification of bridge blockage relies on bridge statistics alone, and we demonstrate that user reports allow us to defend against this attack.
dc.identifier.urihttps://hdl.handle.net/10012/21005
dc.language.isoen
dc.pendingfalse
dc.publisherUniversity of Waterlooen
dc.subjectcensorship circumvention
dc.subjectTor
dc.subjectbridges
dc.titleTroll Patrol: Detecting Blocked Tor Bridges
dc.typeMaster Thesis
uws-etd.degreeMaster of Mathematics
uws-etd.degree.departmentDavid R. Cheriton School of Computer Science
uws-etd.degree.disciplineComputer Science
uws-etd.degree.grantorUniversity of Waterlooen
uws-etd.embargo.terms0
uws.comment.hiddenI applied a Creative Commons license for my thesis. This practice has been approved for previous theses, including those by Nik Unger (https://uwspace.uwaterloo.ca/items/0bef20b7-6996-4801-b0a1-e9096bab8c8d), Justin Tracey (https://uwspace.uwaterloo.ca/items/c134ef2b-2223-4a69-a5d9-da4eece4f60b), and Lindsey Tulloch (https://uwspace.uwaterloo.ca/items/89ea28dd-d67d-4472-9bfc-5e3494c0a98e). Based on this precedent, I believe this should not be a problem.
uws.contributor.advisorGoldberg, Ian
uws.contributor.affiliation1Faculty of Mathematics
uws.peerReviewStatusUnrevieweden
uws.published.cityWaterlooen
uws.published.countryCanadaen
uws.published.provinceOntarioen
uws.scholarLevelGraduateen
uws.typeOfResourceTexten

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