Title | ||
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Accessible Privacy-Preserving Web-Based Data Analysis for Assessing and Addressing Economic Inequalities. |
Abstract | ||
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An essential component of initiatives that aim to address pervasive inequalities of any kind is the ability to collect empirical evidence of both the status quo baseline and of any improvement that can be attributed to prescribed and deployed interventions. Unfortunately, two substantial barriers can arise preventing the collection and analysis of such empirical evidence: (1) the sensitive nature of the data itself and (2) a lack of technical sophistication and infrastructure available to both an initiativeu0027s beneficiaries and to those spearheading it. In the last few years, it has been shown that a cryptographic primitive called secure multi-party computation (MPC) can provide a natural technological resolution to this conundrum. MPC allows an otherwise disinterested third party to contribute its technical expertise and resources, to avoid incurring any additional liabilities itself, and (counterintuitively) to reduce the level of data exposure that existing parties must accept to achieve their data analysis goals. However, achieving these benefits requires the deliberate design of MPC tools and frameworks whose level of accessibility to non-technical users with limited infrastructure and expertise is state-of-the-art. We describe our own experiences designing, implementing, and deploying such usable web applications for secure data analysis within the context of two real-world initiatives that focus on promoting economic equality. |
Year | Venue | Field |
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2018 | COMPASS | Secure multi-party computation,Empirical evidence,Status quo,Computer science,Usability,Risk analysis (engineering),Cryptographic primitive,Equity (economics),Web application,Sophistication |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
18 | 7 |
Name | Order | Citations | PageRank |
---|---|---|---|
Andrei Lapets | 1 | 75 | 10.53 |
Frederick Jansen | 2 | 2 | 2.13 |
Kinan Dak Albab | 3 | 0 | 1.01 |
Rawane Issa | 4 | 1 | 1.70 |
Lucy Qin | 5 | 1 | 1.70 |
Mayank Varia | 6 | 110 | 15.89 |
Azer Bestavros | 7 | 3791 | 764.82 |