Advanced Homomorphic Encryption its Applications and Derivatives (AHEAD)

2013 ◽  
Author(s):  
Tal Rabin ◽  
Nigel Smart ◽  
Daniel Wichs ◽  
Craig Gentry ◽  
Zvika Brakerski ◽  
...  
Keyword(s):  
Homomorphic Encryption

Quantum Error Correction Code Scheme used for Homomorphic Encryption like Quantum Computation

2019 ◽  
Vol 19 (3) ◽  
pp. 61-70
Author(s):  
Il Kwon Sohn ◽  
◽  
Jonghyun Lee ◽  
Wonhyuk Lee ◽  
Woojin Seok ◽  
...  
Keyword(s):  
Error Correction ◽  
Quantum Computation ◽  
Homomorphic Encryption ◽  
Quantum Error Correction ◽  
Code Scheme ◽  
Error Correction Code ◽  
Quantum Error

A Neural Network Application of Fully Homomorphic Encryption for Cloud Computing

2020 ◽  
Author(s):  
Megha Kolhekar ◽  
Ashish Pandey ◽  
Ayushi Raina ◽  
Rijin Thomas ◽  
Vaibhav Tiwari ◽  
...  
Keyword(s):  
Neural Network ◽  
Cloud Computing ◽  
Homomorphic Encryption ◽  
Fully Homomorphic Encryption ◽  
Network Application

Low Size Cipher Text Homomorphic Encryption Scheme for Cloud Data

2017 ◽  
Vol 4 (1) ◽  
pp. 13-20
Author(s):  
Manish M. Potey ◽  
◽  
C. A. Dhote ◽  
Deepak H. Sharma ◽  
◽  
...  
Keyword(s):  
Homomorphic Encryption ◽  
Encryption Scheme ◽  
Cloud Data ◽  
Cipher Text

A fully homomorphic encryption based on magic number fragmentation and El‐Gamal encryption: Smart healthcare use case

2021 ◽  
Author(s):  
Mostefa Kara ◽  
Abdelkader Laouid ◽  
Mohammed Amine Yagoub ◽  
Reinhardt Euler ◽  
Saci Medileh ◽  
...  
Keyword(s):  
Homomorphic Encryption ◽  
Magic Number ◽  
Use Case ◽  
Healthcare Use ◽  
Fully Homomorphic Encryption ◽  
Smart Healthcare

Secure Fingerprint Authentication with Homomorphic Encryption

2020 ◽  
Author(s):  
Wencheng Yang ◽  
Song Wang ◽  
Kan Yu ◽  
James Jin Kang ◽  
Michael N. Johnstone
Keyword(s):  
Homomorphic Encryption

scholarly journals Efficient Private Conjunctive Query Protocol Over Encrypted Data

Cryptography ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 2
Author(s):  
Tushar Kanti Saha ◽  
Takeshi Koshiba
Keyword(s):  
Homomorphic Encryption ◽  
Data Access ◽  
Conjunctive Query ◽  
Conjunctive Queries ◽  
Private Data ◽  
Binary Format ◽  
Main Technique ◽  
Batch Technique ◽  
Outsourced Database ◽  
Packing Method

Conjunctive queries play a key role in retrieving data from a database. In a database, a query containing many conditions in its predicate, connected by an “and/&/∧” operator, is called a conjunctive query. Retrieving the outcome of a conjunctive query from thousands of records is a heavy computational task. Private data access to an outsourced database is required to keep the database secure from adversaries; thus, private conjunctive queries (PCQs) are indispensable. Cheon, Kim, and Kim (CKK) proposed a PCQ protocol using search-and-compute circuits in which they used somewhat homomorphic encryption (SwHE) for their protocol security. As their protocol is far from being able to be used practically, we propose a practical batch private conjunctive query (BPCQ) protocol by applying a batch technique for processing conjunctive queries over an outsourced database, in which both database and queries are encoded in binary format. As a main technique in our protocol, we develop a new data-packing method to pack many data into a single polynomial with the batch technique. We further enhance the performances of the binary-encoded BPCQ protocol by replacing the binary encoding with N-ary encoding. Finally, we compare the performance to assess the results obtained by the binary-encoded BPCQ protocol and the N-ary-encoded BPCQ protocol.

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