Pixel-Batched Homomorphic Encryption for Secure Outsourced Image Convolution

Abstract

Secure outsourced image processing requires a workflow where a data owner wants to simultaneously keep her imagery private while providing it to another party for storage and computation. A key challenge involves allowing the other party to perform meaningful computations on behalf of the data owner. Over the last ten years, homomorphic encryption research addressing this challenge has blossomed. Owing to the fundamental nature of convolution in image processing, we address the problem of secure outsourced image convolution. We start by developing an approach based on a straight-forward application of the Paillier cryptosystem where each pixel is encrypted separately. We improve upon this approach by batching vectors of pixels before encryption (an idea applied by others to different image processing algorithms). We carried out a series of experiments and observed the approach involving batching to require one to two orders of magnitude less computation time.

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Document Details

Document Type
Technical Report
Publication Date
Oct 19, 2020
Accession Number
AD1156987

Entities

People

  • Adrian V Mariano
  • Chris R Giannella
  • James H Tanis

Organizations

  • MITRE Corporation

Tags

Communities of Interest

  • Cyber
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence Software
  • Cloud Storage
  • Computations
  • Computer Science
  • Computer Vision
  • Computers
  • Convolution
  • Convolutional Neural Networks
  • Cryptography
  • Cybersecurity
  • Feature Extraction
  • Image Processing
  • Information Security
  • Neural Networks
  • Personnel Management
  • Security

Fields of Study

  • Computer science
  • Mathematics

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Cybersecurity.
  • Image Processing and Computer Vision.