Alex Pentland

Alexander Lipton

Thomas Hardjono

How to empower people and communities with user-centric data ownership, transparent and accountable algorithms, and secure digital transaction systems. Data is now central to the economy, government, and health systems—so why are data and the AI systems that interpret the data in the hands of so few people? Building the New Economy calls for us to reinvent the ways that data and artificial intelligence are used in civic and government systems. Arguing that we need to think about data as a new type of capital, the authors show that the use of data trusts and distributed ledgers can empower people and communities with user-centric data ownership, transparent and accountable algorithms, machine learning fairness principles and methodologies, and secure digital transaction systems. It’s well known that social media generate disinformation and that mobile phone tracking apps threaten privacy. But these same technologies may also enable the creation of more agile systems in which power and decision-making are distributed among stakeholders rather than concentrated in a few hands. Offering both big ideas and detailed blueprints, the authors describe such key building blocks as data cooperatives, tokenized funding mechanisms, and tradecoin architecture. They also discuss technical issues, including how to build an ecosystem of trusted data, the implementation of digital currencies, and interoperability, and consider the evolution of computational law systems.

Data as Capital

Building the New Economy

David L. Shrier

How to create an Internet of Trusted Data in which insights from data can be extracted without collecting, holding, or revealing the underlying data. 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. Contributors Michiel Bakker, Yves-Alexandre de Montjoye, Daniel Greenwood, Thomas Hardjoni, Jake Kendall, Cameron Kerry, Bruno Lepri, Alexander Lipton, Takeo Nishikata, Alejandro Noriega-Campero, Nuria Oliver, Alex Pentland, David L. Shrier, Jacopo Staiano, Guy Zyskind An MIT Connection Science and Engineering Book

A New Framework for Identity and Data Sharing

Trusted Data, revised and expanded edition

Lakshminath R. Dondeti

A handbook for engineers, architects and other practitioners working in the field of Internet security. It presents detailed coverage of security technologies and techniques for IP (Internet protocol) multicast networks, along with algorithms and protocols for multi-party secure communication.

Multicast and Group Security

Providing a thorough explanation of the risks associated with WLAN and WMAN networks along with detailed descriptions of solutions to a range of security problems, this volume explains the hands-on techniques needed to secure both business and domestic wireless networks.

Security in Wireless LANs and MANs

As the economy and society move from a world where interactions were physical and based on paper documents, toward a world that is primarily governed by digital data and digital transactions, our existing methods of managing identity and data security are proving inadequate. Large-scale fraud, identity theft and data breaches are becoming common, and a large fraction of the population have only the most limited digital credentials. Even so, our digital infrastructure is recognized as a strategic asset which must be resilient to threat. If we can create an Internet of Trusted Data that provides safe, secure access for everyone, then huge societal benefits can be unlocked, including better health, greater financial inclusion, and a population that is more engaged with and better supported by its government. Some of the world's leading data scientists, led by MIT Professor Alex Pentland, describe a roadmap and platforms to implement this new paradigm.

Trust::Data

Jennifer Seberry

Josef Pieprzyk

This reference work looks at modern concepts of computer security. It introduces the basic mathematical background necessary to follow computer security concepts before moving on to modern developments in cryptography. The concepts are presented clearly and illustrated by numerous examples. Subjects covered include: private-key and public-key encryption, hashing, digital signatures, authentication, secret sharing, group-oriented cryptography, and many others. The section on intrusion detection and access control provide examples of security systems implemented as a part of operating system. Database and network security is also discussed. The final chapters introduce modern e- business systems based on digital cash.

Thomas Hardjono

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