“Privacy and Security Projects (active or otherwise).
|SHARP Logical Rep||Automated Policy: Logical Representation of Privacy Laws||The complexity of regulations in healthcare and other industries makes it difficult for enterprises to design and deploy effective compliance systems. We aim to support compliance efforts by using formalized portions of applicable laws to help regulate business processes that use information systems.||John C. Mitchell|
|SecurityOntology.com||SecurityOntology project of XYLEM Technologies||"SecOnt - and its application within the risk management framework AURUM - provides a unified and machine-readable information security knowledge sharing approach, enabling users to collaboratively understand and extend the knowledge body."|
|IEEE and IoT End to end Trust||End to End Trust Meeting||IEEE Meeting held 2016-02|
|IEEE Internet Initiative||IEEE Internet Initiative|
|Privacy-Enhanced Identity Federation||NIST Privacy-Enhanced Identity Federation||We released a white paper describing the challenge, real-world scenarios, potential solutions, and relevant standards for this project. This white paper was open for public comment for 45 days and closed on December 18, 2015. We are now reviewing public comments and will publish a revised white paper shortly. |
You may still download the Privacy-Enhanced Identity Brokers white paper (PDF) or read our two-page fact sheet for more information.
|NASBE Education Data Privacy||NASBE Education Data Privacy||NASBE’s project on Education Data Privacy focuses on supporting state boards of education seeking to create or implement stronger state privacy policies through publications, webinars, collaboration with other privacy and education organizations, in-state and regional meetings, and sessions at our national meetings.||NASBE, Amelia Vance|
|Enigma: Decentralized Computation Platform with Guaranteed Privacy||MIT Enigma: Decentralized Computation Platform with Guaranteed Privacy||A peer-to-peer network, enabling different parties to jointly store and run computations|
on data while keeping the data completely private. Enigma’s computational
model is based on a highly optimized version of secure multi-party computation,
guaranteed by a verifiable secret-sharing scheme. For storage, we use a modi-
fied distributed hashtable for holding secret-shared data. An external blockchain
is utilized as the controller of the network, manages access control, identities and
serves as a tamper-proof log of events. Security deposits and fees incentivize operation,
correctness and fairness of the system. Similar to Bitcoin, Enigma removes
the need for a trusted third party, enabling autonomous control of personal data.
For the first time, users are able to share their data with cryptographic guarantees
regarding their privacy
|Guy Zyskind, Oz Nathan, Alex ’Sandy’ Pentland|