Computing Community Consortium Blog

The goal of the Computing Community Consortium (CCC) is to catalyze the computing research community to debate longer range, more audacious research challenges; to build consensus around research visions; to evolve the most promising visions toward clearly defined initiatives; and to work with the funding organizations to move challenges and visions toward funding initiatives. The purpose of this blog is to provide a more immediate, online mechanism for dissemination of visioning concepts and community discussion/debate about them.

Privacy in Information-Rich Intelligent Infrastructure

June 6th, 2017 / in Announcements, CCC, research horizons, Research News / by Helen Wright

Did you know that driverless cars communicate real-time location and other data to cloud aggregators like Google? This intelligent infrastructure monitoring compromises the privacy of drivers who continuously share their locations. Without a framework for protecting the privacy of the driver’s data, drivers will be very conservative about sharing their data. This data, however, is a necessity for adding the intelligence to intelligent infrastructure.

Recently, the Computing Community Consortium (CCC) in collaboration with the Electrical and Computer Engineering Department Heads Association (ECEDHA) released white papers describing a collective research agenda for intelligent infrastructure. Today, we highlight a new paper that was just released called the Privacy in Information-Rich Intelligent Infrastructure paper.

We will be blogging about each paper over the next few weeks.

The more data we have the more intelligent our infrastructure will be, but also the less privacy we can provide to the owners of the data. It is hence critical to understand the tradeoff between intelligence and privacy in the context of infrastructure.

Over the past decade, there has been a major scientific breakthrough in better understanding privacy from a scientific point of view. Differential privacy has emerged as a very strong notion of privacy that allows us to think of the fundamental limits of what can be inferred by a malicious agent that has access to public information. This has led to a flurry of research activity the privacy of many basic algorithms. While differential privacy ensures privacy of the information in data, we must consider additional measure of privacy at the level of communications as well as computation that manipulate the data.

Furthermore, this white paper argues that there are unique scientific challenges that arise in the context of intelligent infrastructures such as privacy for streaming IoT-data, decentralized privacy, variable privacy, and fundamental privacy limits.

The paper recommends the following actions:

  • Infrastructure Data
    • Recommend the development of a depository for IoT-data that is monitoring different infrastructure sectors (transportation, energy, water, etc.).
  • Joint Funding Initiative
    • Develop a joint interagency research program across relevant agencies (NSF, DoT, DoE, DHS) where fundamental scientific advances are funded by NSF whereas the contextualization of such principles and algorithms are funded by relevant sectors (DoE for SmartGrid Privacy, DoT for transportation privacy, etc.).
  • National Epsilon Registry
    • Differential privacy provides a measure of privacy loss, typically called (“epsilon”). An “Epsilon Registry” is proposed, in which firms and websites that traffic in personal information would record details about their treatment of data.
  • Data Property Rights
    • Defining property rights over data and information will be very important both in protecting data owners but also in creating a new economy for data.
  • Privacy Forum
    • Privacy requires a continuing discussion among regulators, legal experts, privacy experts, as well as corporations in order to balance the scientific feasibility of privacy with social norms of privacy.

These recommendations come at an opportune time. Recently, U.S. Sen. Ron Wyden pushed a federal panel to recommend that strong data security measures be employed by government agencies collecting and analyzing personal information in an upcoming report to Congress on evidence-based policymaking. In a letter to the Commission on Evidence-Based Policymaking, Wyden stressed the need to use privacy-enhancing technologies (PETs) to protect private data that is collected and stored in government databases.

Please read the paper for additional details on the research agenda on privacy in intelligent infrastructure.

Stay tuned to learn more about the other intelligent infrastructure papers!

Privacy in Information-Rich Intelligent Infrastructure

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