scispace - formally typeset
K

Kuaikuai Duan

Publications -  12
Citations -  216

Kuaikuai Duan is an academic researcher. The author has contributed to research in topics: Encryption & Medicine. The author has an hindex of 4, co-authored 5 publications receiving 172 citations.

Papers
More filters
Journal ArticleDOI

Asymmetric double-image encryption based on cascaded discrete fractional random transform and logistic maps

TL;DR: A double-image encryption is proposed based on the discrete fractional random transform and logistic maps that has high resistance against to the potential attacks such as chosen plaintext attack.
Journal ArticleDOI

Double-image encryption based on discrete multiple-parameter fractional angular transform and two-coupled logistic maps

TL;DR: A new discrete fractional transform defined by the fractional order, periodicity and vector parameters is presented, which is named as the discrete multiple-parameter fractional angular transform and a double-image encryption scheme is proposed, which has an obvious advantage that no phase keys are used in the encryption and decryption process.
Journal ArticleDOI

Asymmetric multiple-image encryption based on coupled logistic maps in fractional Fourier transform domain

TL;DR: The peak signal-to-noise is used to evaluate the quality of the decrypted image, which shows that the encryption capacity of the proposed scheme is enhanced considerably and has high security against various attacks, such as chosen plaintext attack.
Journal ArticleDOI

A secure double-image sharing scheme based on Shamir׳s three-pass protocol and 2D Sine Logistic modulation map in discrete multiple-parameter fractional angular transform domain

TL;DR: Simulation results and security analysis verify the feasibility and effectiveness of the proposed double-image sharing scheme using the Shamir’s three-pass protocol in the discrete multiple-parameter fractional angular transform domain.
Proceedings ArticleDOI

A deep generative multimodal imaging genomics framework for Alzheimer's disease prediction

TL;DR: In this article , a deep multimodal generative data fusion framework for integrating these sources in a classification task involving Alzheimer's disease patients and healthy controls from the ADNI database is presented.