The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
May. 19, 2026

Filed:

Jan. 17, 2020
Applicant:

The Regents of the University of California, Oakland, CA (US);

Inventors:

Mohammad Sadegh Riazi, San Diego, CA (US);

Farinaz Koushanfar, San Diego, CA (US);

Mohammad Samragh Razlighi, San Diego, CA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/082 (2023.01); G06F 21/71 (2013.01); G06N 3/04 (2023.01);
U.S. Cl.
CPC ...
G06N 3/082 (2013.01); G06F 21/71 (2013.01); G06N 3/04 (2013.01);
Abstract

A framework is presented that provides a shift in the conceptual and practical realization of privacy-preserving interference on deep neural networks. The framework leverages the concept of the binary neural networks (BNNs) in conjunction with the garbled circuits protocol. In BNNs, the weights and activations are restricted to binary (e.g., ±1) values, substituting the costly multiplications with simple XNOR operations during the inference phase. The XNOR operation is known to be free in the GC protocol; therefore, performing oblivious inference on BNNs using GC results in the removal of costly multiplications. The approach consistent with implementations of the current subject matter provides for oblivious inference on the standard DL benchmarks being performed with minimal, if any, decrease in the prediction accuracy.


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