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Vuvuzela : scalable private messaging that hides metadata

Author(s)
Lazar, David, Ph.D. Massachusetts Institute of Technology
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Alternative title
Scalable private messaging that hides metadata
Other Contributors
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Nickolai Zeldovich.
Terms of use
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582
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Abstract
Private messaging over the Internet has proven challenging to implement, because even if message data is encrypted, it is difficult to hide metadata about who is communicating in the face of traffic analysis. Systems that offer strong privacy guarantees, such as Dissent [39], scale to only several thousand clients, because they use techniques with superlinear cost in the number of clients (e.g., each client broadcasts their message to all other clients). On the other hand, scalable systems, such as Tor, do not protect against traffic analysis, making them ineffective in an era of pervasive network monitoring. Vuvuzela is a new scalable messaging system that offers strong privacy guarantees, hiding both message data and metadata. Vuvuzela is secure against adversaries that observe and tamper with all network traffic, and that control all nodes except for one server. Vuvuzela's key insight is to minimize the number of variables observable by an attacker, and to use differential privacy techniques to add noise to all observable variables in a way that provably hides information about which users are communicating. Vuvuzela has a linear cost in the number of clients, and experiments show that it can achieve a throughput of 68,000 messages per second for 1 million users with a 37-second end-to-end latency on commodity servers.
Description
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
 
Cataloged from PDF version of thesis.
 
Includes bibliographical references (pages 57-60).
 
Date issued
2016
URI
http://hdl.handle.net/1721.1/103748
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

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