Dissertation/Thesis Abstract

Toward Automated Worldwide Monitoring of Network-Level Censorship
by Weinberg, Zachary, Ph.D., Carnegie Mellon University, 2018, 112; 13425933
Abstract (Summary)

Although Internet censorship is a well-studied topic, to date most published studies have focused on a single aspect of the phenomenon, using methods and sources specific to each researcher. Results are difficult to compare, and global, historical perspectives are rare. Because each group maintains their own software, erroneous methods may continue to be used long after the error has been discovered. Because censors continually update their equipment and blacklists, it may be impossible to reproduce historical results even with the same vantage points and testing software. Because “probe lists” of potentially censored material are labor-intensive to compile, requiring an understanding of the politics and culture of each country studied, researchers discover only the most obvious and long-lasting cases of censorship.

In this dissertation I will show that it is possible to make progress toward addressing all of these problems at once. I will present a proof-of concept monitoring system designed to operate continuously, in as many different countries as possible, using the best known techniques for detection and analysis. I will also demonstrate improved techniques for verifying the geographic location of a monitoring vantage point; for distinguishing innocuous network problems from censorship and other malicious network interference; and for discovering new web pages that are closely related to known-censored pages. These techniques improve the accuracy of a continuous monitoring system and reduce the manual labor required to operate it.

This research has, in addition, already led to new discoveries. For example, I have confirmed reports that a commonly-used heuristic is too sensitive and will mischaracterize a wide variety of unrelated problems as censorship. I have been able to identify a few cases of political censorship within a much longer list of cases of moralizing censorship. I have expanded small seed groups of politically sensitive documents into larger groups of documents to test for censorship. Finally, I can also detect other forms of network interference with a totalitarian motive, such as injection of surveillance scripts.

In summary, this work demonstrates that mostly-automated measurements of Internet censorship on a worldwide scale are feasible, and that the elusive global and historical perspective is within reach.

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Indexing (document details)
Advisor: Christin, Nicolas
Commitee: Bauer, Lujo, Gill, Phillipa, Sekar, Vyas
School: Carnegie Mellon University
Department: Electrical and Computer Engineering
School Location: United States -- Pennsylvania
Source: DAI-B 80/05(E), Dissertation Abstracts International
Source Type: DISSERTATION
Subjects: Public policy, Computer science
Keywords: Censorship, Geolocation, Network monitoring, Networking
Publication Number: 13425933
ISBN: 9780438792135
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