Privacy Changes Everything

Jennie Rogers*, Johes Bater, Xi He, Ashwin Machanavajjhala, Madhav Suresh, Xiao Wang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We are storing and querying datasets with the private information of individuals at an unprecedented scale in settings ranging from IoT devices in smart homes to mining enormous collections of click trails for targeted advertising. Here, the privacy of the people described in these datasets is usually addressed as an afterthought, engineered on top of a DBMS optimized for performance. At best, these systems support security or managing access to sensitive data. This status quo has brought us a plethora of data breaches in the news. In response, governments are stepping in to enact privacy regulations such as the EU’s GDPR. We posit that there is an urgent need for trustworthy database system that offer end-to-end privacy guarantees for their records with user interfaces that closely resemble that of a relational database. As we shall see, these guarantees inform everything in the database’s design from how we store data to what query results we make available to untrusted clients. In this position paper we first define trustworthy database systems and put their research challenges in the context of relevant tools and techniques from the security community. We then use this backdrop to walk through the “life of a query” in a trustworthy database system. We start with the query parsing and follow the query’s path as the system plans, optimizes, and executes it. We highlight how we will need to rethink each step to make it efficient, robust, and usable for database clients.

Original languageEnglish (US)
Title of host publicationHeterogeneous Data Management, Polystores, and Analytics for Healthcare - VLDB 2019 Workshops, Poly and DMAH, Los Angeles, CA, USA, August 30, 2019, Revised Selected Papers
EditorsVijay Gadepally, Timothy Mattson, Michael Stonebraker, Fusheng Wang, Gang Luo, Yanhui Laing, Alevtina Dubovitskaya
PublisherSpringer
Pages96-111
Number of pages16
ISBN (Print)9783030337513
DOIs
StatePublished - 2019
EventInternational Workshops on Polystores and other Systems for Heterogeneous Data, Poly 2018, and Data Management and Analytics for Medicine and Healthcare, DMAH 2018 held in conjunction with the 44th International Conference on Very Large Data Bases, VLDB 2018 - Los Angeles, United States
Duration: Aug 30 2019Aug 30 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11721 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Workshops on Polystores and other Systems for Heterogeneous Data, Poly 2018, and Data Management and Analytics for Medicine and Healthcare, DMAH 2018 held in conjunction with the 44th International Conference on Very Large Data Bases, VLDB 2018
CountryUnited States
CityLos Angeles
Period8/30/198/30/19

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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