Efficient fully homomorphic encryption with circularly secure key switching process

2016 ◽  
Vol 9 (5/6) ◽  
pp. 417 ◽  
Author(s):  
Tanping Zhou ◽  
Xiaoyuan Yang ◽  
Wei Zhang ◽  
Liqiang Wu
Keyword(s):  
Homomorphic Encryption ◽  
Switching Process ◽  
Fully Homomorphic Encryption ◽  
Key Switching

Efficient RLWE-Based Multi-key Fully Homomorphic Encryption Without Key-Switching

2021 ◽  
pp. 323-342
Author(s):  
Xiaoliang Che ◽  
Yao Liu ◽  
Shangwen Zheng ◽  
Longfei Liu ◽  
Tanping Zhou ◽  
...  
Keyword(s):  
Homomorphic Encryption ◽  
Fully Homomorphic Encryption ◽  
Key Switching

scholarly journals Modified multi-key fully homomorphic encryption based on NTRU cryptosystem without key-switching

2020 ◽  
Vol 25 (5) ◽  
pp. 564-578
Author(s):  
Xiaoliang Che ◽  
Tanping Zhou ◽  
Ningbo Li ◽  
Haonan Zhou ◽  
Zhenhua Chen ◽  
...  
Keyword(s):  
Homomorphic Encryption ◽  
Fully Homomorphic Encryption ◽  
Key Switching

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

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

scholarly journals A Password Meter without Password Exposure

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 345
Author(s):  
Pyung Kim ◽  
Younho Lee ◽  
Youn-Sik Hong ◽  
Taekyoung Kwon
Keyword(s):  
Performance Enhancement ◽  
Homomorphic Encryption ◽  
Optimization Techniques ◽  
Third Party ◽  
Fully Homomorphic Encryption ◽  
Performance Achievement ◽  
Server Side ◽  
On Line ◽  
Internal Mechanism ◽  
High Chance

To meet password selection criteria of a server, a user occasionally needs to provide multiple choices of password candidates to an on-line password meter, but such user-chosen candidates tend to be derived from the user’s previous passwords—the meter may have a high chance to acquire information about a user’s passwords employed for various purposes. A third party password metering service may worsen this threat. In this paper, we first explore a new on-line password meter concept that does not necessitate the exposure of user’s passwords for evaluating user-chosen password candidates in the server side. Our basic idea is straightforward; to adapt fully homomorphic encryption (FHE) schemes to build such a system but its performance achievement is greatly challenging. Optimization techniques are necessary for performance achievement in practice. We employ various performance enhancement techniques and implement the NIST (National Institute of Standards and Technology) metering method as seminal work in this field. Our experiment results demonstrate that the running time of the proposed meter is around 60 s in a conventional desktop server, expecting better performance in high-end hardware, with an FHE scheme in HElib library where parameters support at least 80-bit security. We believe the proposed method can be further explored and used for a password metering in case that password secrecy is very important—the user’s password candidates should not be exposed to the meter and also an internal mechanism of password metering should not be disclosed to users and any other third parties.

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