<abstract xmlns="http://www.w3.org/1999/xhtml"><p> Medical volume data containing patient information is often faced with various attacks in the transmission process. In order to enhance the medical information system security, and effectively solve the problem of medical volume data protection, a new zero-watermarking algorithm is proposed in the paper. The new zero-watermarking algorithm takes advantage of three-dimensional discrete wavelet transform multi-resolution analysis characteristics of space and time, threedimensional discrete cosine transform properties, and differences hashing robust characteristic. In order to enhance watermarking algorithm security, Legendre chaotic neural network is used for scrambling original watermark image. The medical volume data is made by three-dimensional discrete wavelet transform, threedimensional discrete cosine transform and three-dimensional discrete inverse cosine transform r to obtain the medical volume data feature matrix (4×5×4), which is converted to 64-bit binary feature sequence through difference hashing algorithm. The 64-bit binary feature sequence is used to construct the zero-watermarking. The experimental results prove that the new zero-watermarking has favorable security and robustness resisting various attacks. Therefore, the new zero-watermarking algorithm is more applicable to protect medical volume data.</p></abstract>

Medical volume data containing patient information is often faced with various attacks in the transmission process. In order to enhance the medical information system security, and effectively solve the problem of medical volume data protection, a new zero-watermarking algorithm is proposed in the paper. The new zero-watermarking algorithm takes advantage of three-dimensional discrete wavelet transform multi-resolution analysis characteristics of space and time, threedimensional discrete cosine transform properties, and differences hashing robust characteristic. In order to enhance watermarking algorithm security, Legendre chaotic neural network is used for scrambling original watermark image. The medical volume data is made by three-dimensional discrete wavelet transform, threedimensional discrete cosine transform and three-dimensional discrete inverse cosine transform r to obtain the medical volume data feature matrix (4×5×4), which is converted to 64-bit binary feature sequence through difference hashing algorithm. The 64-bit binary feature sequence is used to construct the zero-watermarking. The experimental results prove that the new zero-watermarking has favorable security and robustness resisting various attacks. Therefore, the new zero-watermarking algorithm is more applicable to protect medical volume data.

A New Zero-Watermarking Algorithm Resisting Attacks Based on Differences Hashing

College of Information Science and Technology, Hainan University, Haikou, 570228 China

Hainan Software Profession Institute, Qionghai, 571400 China

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"A New Zero-Watermarking Algorithm Resisting Attacks Based on Differences Hashing"}

Medical volume data containing patient information is often faced with various attacks in the transmission process. In order to enhance the medical information...

A New Zero-Watermarking Algorithm Resisting Attacks Based on Differences Hashing

Published Online: Jun 22, 2016

Page range: 135 - 147

DOI: https://doi.org/10.1515/cait-2016-0026

Keywords
Zero-watermarking algorithm, scrambling, medical volume data, three-dimensional discrete inverse cosine transform, difference hashing

© by Baoru Han

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

A New Zero-Watermarking Algorithm Resisting Attacks Based on Differences Hashing

Published Online: Jun 22, 2016

Page range: 135 - 147

DOI: https://doi.org/10.1515/cait-2016-0026

KeywordsZero-watermarking algorithm, scrambling, medical volume data, three-dimensional discrete inverse cosine transform, difference hashing

© by Baoru Han

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Keywords
Zero-watermarking algorithm, scrambling, medical volume data, three-dimensional discrete inverse cosine transform, difference hashing