H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 30 Citations 3,053 117 World Ranking 8791 National Ranking 829

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Algorithm
  • Cryptography

His primary areas of investigation include Encryption, Theoretical computer science, Cryptosystem, Algorithm and Image. His work carried out in the field of Encryption brings together such families of science as Permutation, Cryptography and Compressed sensing. His Theoretical computer science research includes elements of Ciphertext-only attack, Pixel and Probabilistic encryption.

His studies deal with areas such as Stream cipher, Communication channel, Chaotic map and Confusion and diffusion as well as Cryptosystem. His Algorithm research is multidisciplinary, incorporating perspectives in Chaotic, Encoding and Robustness. His study in Image is interdisciplinary in nature, drawing from both Homomorphic encryption, Probabilistic logic and Homomorphism.

His most cited work include:

  • An image encryption scheme based on rotation matrix bit-level permutation and block diffusion (154 citations)
  • Double optical image encryption using discrete Chirikov standard map and chaos-based fractional random transform (141 citations)
  • Exploiting self-adaptive permutation–diffusion and DNA random encoding for secure and efficient image encryption (138 citations)

What are the main themes of his work throughout his whole career to date?

His scientific interests lie mostly in Encryption, Algorithm, Image, Compressed sensing and Theoretical computer science. His Encryption study integrates concerns from other disciplines, such as Chaotic, Artificial intelligence and Key. In his work, Phase is strongly intertwined with Encoding, which is a subfield of Algorithm.

The Image study combines topics in areas such as CHAOS and Data mining. His Compressed sensing course of study focuses on Decoding methods and Distributed computing. His research integrates issues of Plaintext, Ciphertext-only attack, Probabilistic encryption, Key schedule and Robustness in his study of Theoretical computer science.

He most often published in these fields:

  • Encryption (86.79%)
  • Algorithm (50.94%)
  • Image (41.51%)

What were the highlights of his more recent work (between 2019-2021)?

  • Encryption (86.79%)
  • Artificial intelligence (32.70%)
  • Cipher (30.82%)

In recent papers he was focusing on the following fields of study:

Yushu Zhang mainly investigates Encryption, Artificial intelligence, Cipher, Image and Computer vision. His Encryption research is multidisciplinary, incorporating elements of Algorithm, Compressed sensing, Hash function and Chaotic. He combines subjects such as Permutation and Confusion and diffusion with his study of Chaotic.

In Cipher, he works on issues like Color image, which are connected to Local binary patterns, Grayscale, Genetic algorithm, Pattern recognition and Crossover. When carried out as part of a general Image research project, his work on Thumbnail is frequently linked to work in Usability, therefore connecting diverse disciplines of study. He works mostly in the field of Computer vision, limiting it down to concerns involving Embedding and, occasionally, Pixel.

Between 2019 and 2021, his most popular works were:

  • An efficient visually meaningful image compression and encryption scheme based on compressive sensing and dynamic LSB embedding (43 citations)
  • An efficient visually meaningful image compression and encryption scheme based on compressive sensing and dynamic LSB embedding (43 citations)
  • An efficient visually meaningful image compression and encryption scheme based on compressive sensing and dynamic LSB embedding (43 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Algorithm
  • Cryptography

His scientific interests lie mostly in Encryption, Artificial intelligence, Hash function, Computer vision and Cipher. His research in Encryption intersects with topics in Algorithm, Compressed sensing, Image and Chaotic. His Compressed sensing research integrates issues from Image compression and Feature.

His studies in Artificial intelligence integrate themes in fields like Machine learning and Threat model. His research brings together the fields of Embedding and Computer vision. His Cipher research incorporates themes from Pixel, Grayscale, Kronecker product, Color image and Local binary patterns.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Exploiting self-adaptive permutation–diffusion and DNA random encoding for secure and efficient image encryption

Junxin Chen;Zhi-liang Zhu;Li-bo Zhang;Yushu Zhang.
Signal Processing (2018)

190 Citations

A Review of Compressive Sensing in Information Security Field

Yushu Zhang;Leo Yu Zhang;Jiantao Zhou;Licheng Liu.
IEEE Access (2016)

161 Citations

A visually secure image encryption scheme based on compressive sensing

Xiuli Chai;Zhihua Gan;Yiran Chen;Yushu Zhang.
Signal Processing (2017)

150 Citations

Embedding cryptographic features in compressive sensing

Yushu Zhang;Jiantao Zhou;Fei Chen;Leo Yu Zhang.
Neurocomputing (2016)

102 Citations

An efficient image encryption scheme using lookup table-based confusion and diffusion

Jun-xin Chen;Zhi-liang Zhu;Chong Fu;Li-bo Zhang.
Nonlinear Dynamics (2015)

90 Citations

On the Security of a Class of Diffusion Mechanisms for Image Encryption

Leo Yu Zhang;Yuansheng Liu;Fabio Pareschi;Yushu Zhang.
IEEE Transactions on Systems, Man, and Cybernetics (2018)

84 Citations

An image encryption scheme using nonlinear inter-pixel computing and swapping based permutation approach

Jun-xin Chen;Zhi-liang Zhu;Chong Fu;Li-bo Zhang.
Communications in Nonlinear Science and Numerical Simulation (2015)

80 Citations

Reversible data hiding in encrypted images using cross division and additive homomorphism

Ming Li;Di Xiao;Yushu Zhang;Hai Nan.
Signal Processing-image Communication (2015)

80 Citations

Bi-level Protected Compressive Sampling

Leo Yu Zhang;Kwok-Wo Wong;Yushu Zhang;Jiantao Zhou.
IEEE Transactions on Multimedia (2016)

73 Citations

An efficient visually meaningful image compression and encryption scheme based on compressive sensing and dynamic LSB embedding

Xiuli Chai;Haiyang Wu;Zhihua Gan;Yushu Zhang;Yushu Zhang;Yushu Zhang.
Optics and Lasers in Engineering (2020)

71 Citations

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Best Scientists Citing Yushu Zhang

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