Trusted data:

Contributor(s):

Material type: Text

TextPublication details: Cambridge: MIT Press, 2019Description: vi, 391pISBN:

9780262043212

Subject(s):

DDC classification:

005.83 TRU

Summary: Trusted Data describes a data architecture that places humans and their societal values at the center of the discussion. By involving people from all parts of the ecosystem of information, this new approach allows us to realize the benefits of data-driven algorithmic decision making while minimizing the risks and unintended consequences. It proposes a software architecture and legal framework for an Internet of Trusted Data that provides safe, secure access for everyone and protects against bias, unfairness, and other unintended effects. This approach addresses issues of data privacy, security, ownership, and trust by allowing insights to be extracted from data held by different people, companies, or governments without collecting, holding, or revealing the underlying data. The software architecture, called Open Algorithms, or OPAL, sends algorithms to databases rather than copying or sharing data. The data is protected by existing firewalls; only encrypted results are shared. Data never leaves its repository. A higher security architecture, ENIGMA, built on OPAL, is fully encrypted.

Item type:

Book

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Holdings
Item type	Current library	Call number	Status	Date due	Barcode
Book	IIM Kashipur	005.83 TRU (Browse shelf(Opens below))	Available		9394

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Previous	005.82 INF Information security and privacy: 19th Australasian Conference, ACISP 2014, Wollongong, NSW, Australia, July 7-9, 2014 proceedings/	005.82 MAR Introduction to identity-based encryption/	005.824 ESS Essentials of blockchain technology/	005.83 TRU Trusted data: a new framework for identity and data sharing/	006.3 Artificial intelligence trends for data analytics using machine learning and deep learning approaches /	006.3/1 Machine learning and analytics in healthcare systems : principles and applications /	006.3/12 Advanced data science and analytics with Python /	Next

Includes bibliographical references and index.

Trusted Data describes a data architecture that places humans and their societal values at the center of the discussion. By involving people from all parts of the ecosystem of information, this new approach allows us to realize the benefits of data-driven algorithmic decision making while minimizing the risks and unintended consequences. It proposes a software architecture and legal framework for an Internet of Trusted Data that provides safe, secure access for everyone and protects against bias, unfairness, and other unintended effects. This approach addresses issues of data privacy, security, ownership, and trust by allowing insights to be extracted from data held by different people, companies, or governments without collecting, holding, or revealing the underlying data. The software architecture, called Open Algorithms, or OPAL, sends algorithms to databases rather than copying or sharing data. The data is protected by existing firewalls; only encrypted results are shared. Data never leaves its repository. A higher security architecture, ENIGMA, built on OPAL, is fully encrypted.

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