My research investigates three questions: How do we customize protocols and implementations to account for the unique requirement of each setting and its target community, what are necessary steps that we can take to transition secure computation tools into practice, and how can we promote their adoption for users at large? In this dissertation I present several of my works that address these three questions with a particular focus on one of them.
First my work on "Hecate: Abuse Reporting in Secure Messengers with Sealed Sender" designs a customized protocol to protect people from abuse and surveillance in online end to end encrypted messaging. Our key insight is to add pre-processing to asymmetric message franking, where the moderating entity can generate batches of tokens per user during off-peak hours that can later be deposited when reporting abuse.
This thesis then demonstrates that by carefully tailoring our cryptographic protocols for real world use cases, we can achieve orders of magnitude improvements over prior works with minimal assumptions over the resources available to people.
Second, my work on "Batched Differentially Private Information Retrieval" contributes a novel Private Information Retrieval (PIR) protocol called DP-PIR that is designed to provide high throughput at high query rates. It does so by pushing all public key operations into an offline stage, batching queries from multiple clients via techniques similar to mixnets, and maintain differential privacy guarantees over the access patterns of the database.
Finally, I provide three case studies showing that we cannot hope to further the adoption of cryptographic tools in practice without collaborating with the very people we are trying to protect. I discuss a pilot deployment of secure multi-party computation (MPC) that I have done with the Department of Education, deployments of MPC I have done for the Boston Women’s Workforce Council and the Greater Boston Chamber of Commerce, and ongoing work in developing tool chain support for MPC via an automated resource estimation tool called Carousels.
Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/46383 |
Date | 23 June 2023 |
Creators | Issa, Rawane |
Contributors | Varia, Mayank |
Source Sets | Boston University |
Language | en_US |
Detected Language | English |
Type | Thesis/Dissertation |
Rights | Attribution 4.0 International, http://creativecommons.org/licenses/by/4.0/ |
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