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Privacy-Friendly Forecasting for the Smart Grid Using Homomorphic Encryption and the Group Method of Data Handling

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Publication:4975187
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DOI10.1007/978-3-319-57339-7_11zbMath1408.94928MaRDI QIDQ4975187

Ilia Iliashenko, Joppe W. Bos, Frederik Vercauteren, Wouter Castryck

Publication date: 4 August 2017

Published in: Progress in Cryptology - AFRICACRYPT 2017 (Search for Journal in Brave)



Mathematics Subject Classification ID

Cryptography (94A60)


Related Items (2)

Homomorphic lower digits removal and improved FHE bootstrapping ⋮ Efficiently processing complex-valued data in homomorphic encryption


Uses Software

  • NFLlib
  • GitHub
  • FV-NFLlib


Cites Work

  • On the concrete hardness of learning with errors
  • Fixed-point arithmetic in SHE schemes
  • NFLlib: NTT-Based Fast Lattice Library
  • Improved Security for a Ring-Based Fully Homomorphic Encryption Scheme
  • On Ideal Lattices and Learning with Errors over Rings
  • Public-Key Cryptosystems Based on Composite Degree Residuosity Classes
  • Fully homomorphic encryption using ideal lattices
  • On Ideal Lattices and Learning with Errors over Rings


This page was built for publication: Privacy-Friendly Forecasting for the Smart Grid Using Homomorphic Encryption and the Group Method of Data Handling

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