Master’s Thesis Presentation • Cryptography, Security, and Privacy (CrySP) • PRSONA: Private Reputation Supporting Ongoing Network Avatars

Friday, November 19, 2021 11:00 am - 11:00 am EST (GMT -05:00)

Please note: This master’s thesis presentation will be given online.

Stan Gurtler, Master’s candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Ian Goldberg

Trust and user-generated feedback have become increasingly vital to the normal functioning of the modern internet. However, deployed systems that currently incorporate such feedback do not guarantee users much in the way of privacy, despite a wide swath of research on how to do so spanning over 15 years. Meanwhile, research on systems that maintain user privacy while helping them to track and update each others’ reputations has failed to standardize terminology, or converge on what privacy guarantees should be important. Too often, this leads to misunderstandings of the tradeoffs underpinning design decisions. Further, key insights made in some approaches to designing such systems have not circulated to other approaches, leaving open significant opportunity for new research directions.

Acknowledging this situation, online communities in particular face a difficult dilemma. Communities generally want to provide opportunities for their members to interact and communicate with one another in ways that advance their mutual interests. At times, communities may identify opportunities where providing their members specific privacy guarantees would particularly aid those opportunities, giving members assurances that their participation would not have negative consequences for themselves. However, communities also face the threat of bad actors, who may wish to disrupt their activities, or even to bring harm to members for their status as members of such groups. The privacy that the community wishes to extend to members must be carefully approached so that bad actors can still be held accountable.

This thesis proceeds in two parts. First, this thesis investigates 47 systems describing privacy-preserving reputation systems from 2003–2021 in order to organize previous work and suggest directions for future work. The three key contributions in this portion of the thesis are the systematization of this body of research, the detailing of the tradeoffs implied by overarching design choices, and the identification of underresearched areas that provide promising opportunities for future work.

Second, this thesis explores one particular opportunity for new research identified in the first section of the thesis. Whereas previous work has overlooked the needs of certain kinds of niche communities, this work features a novel design for a privacy-preserving reputation system which is targeted to fill that gap. The nature of its design is discussed particularly in contrast to the identified patterns of design present in previous works. Further, this thesis implements and benchmarks said system to determine its viability in real-world deployment. This novel construction addresses shortcomings with previous approaches and provides new opportunity to a heretofore underrepresented audience.


To join this master’s thesis presentation on BigBlueButton, please go to https://bbb.crysp.org/b/sta-k4w-2lh-jb5.