SBIR Phase I: Blockchain-Enabled Machine Learning on Confidential Data

Information

  • NSF Award
  • 1914373
Owner
  • Award Id
    1914373
  • Award Effective Date
    7/1/2019 - 5 years ago
  • Award Expiration Date
    12/31/2019 - 5 years ago
  • Award Amount
    $ 224,634.00
  • Award Instrument
    Standard Grant

SBIR Phase I: Blockchain-Enabled Machine Learning on Confidential Data

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project includes advances in scientific understanding and substantial societal and commercial impacts. In an era with seemingly endless data breaches, the project offers a way of applying the power of machine learning while never disclosing sensitive raw data. Decentralized computation can increase the scale of models that may be trained, which will allow the use of deep learning on more complicated problems across a range of fields. Additionally, allowing confidential data to be used will allow more rapid research advances in fields with sensitive data, such as biomedicine. Furthermore, decentralized computation offers the promise of lower cost than existing computational infrastructures such as cloud providers. This greater, and more democratic, power will push the boundaries of the state-of-the-art and also enable more people to leverage large-scale machine learning.<br/><br/>This SBIR Phase I project proposes to advance knowledge in the area of coordinating decentralized secure machine learning with a blockchain in a manner that maintains data confidentiality and ensures verifiability. The R&D will also advance understanding and practicality of zero knowledge computational verification and homomorphic neural networks. While deep neural networks have yielded astounding results in recent years, there has been limited progress towards achieving a practical solution to training models in a decentralized context while both maintaining data confidentiality and ensuring verifiability. This is the key challenge and it is anticipated that this project will yield a solution. The proposed approach involves defining a protocol for training amongst untrusted parties that is mediated by a decentralized ledger and involves the use of homomorphic encryption and a computational verification technique.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

  • Program Officer
    Anna Brady-Estevez
  • Min Amd Letter Date
    6/21/2019 - 5 years ago
  • Max Amd Letter Date
    6/21/2019 - 5 years ago
  • ARRA Amount

Institutions

  • Name
    Onu Technology, Inc.
  • City
    San Jose
  • State
    CA
  • Country
    United States
  • Address
    7280 Blue Hill Dr.
  • Postal Code
    951293624
  • Phone Number
    4087149253

Investigators

  • First Name
    Guha
  • Last Name
    Jayachandran
  • Email Address
    guha@onutechnology.com
  • Start Date
    6/21/2019 12:00:00 AM

Program Element

  • Text
    SBIR Phase I
  • Code
    5371

Program Reference

  • Text
    Chemical Technology
  • Code
    8030