Secure and resilient improved image steganography using hybrid fuzzy neural network with fuzzy logic

扫码查看

原文链接

万方数据

外文摘要：The exponential growth in communication networks,data technology,advanced libraries,and mainly World Wide Web services has played a pivotal role in facilitating the retrieval of various types of information as needed.However,this progress has also led to security concerns related to the transmission of confidential data.Nevertheless,safeguarding these data during communication through insecure channels is crucial for obvious reasons.The emergence of steganography offers a robust approach to concealing confidential information,such as images,audio tracks,text files,and video files,in suitable media carriers.A novel technique is envisioned based on back-propagation learning.According to the proposed method,a hybrid fuzzy neural network(HFNN)is applied to the output obtained from the least significant bit substitution of secret data using pixel value dif-ferences and exploiting the modification direction.Through simulation and test results,it has been observed that the proposed methodology achieves secure steganography and superior visual quality.During the experiments,we observed that for the secret image of the cameraman,the PSNR&MSE values of the proposed technique are 61.963895 and 0.041361,respectively.

外文关键词：

Image enhancementImage processingSteganographyDeep learningFuzzy neural combination

作者：

Sachin Dhawan、Hemanta Kumar Bhuyan、Subhendu Kumar Pani、Vinayakumar Ravi、Rashmi Gupta、Arun Rana、Alanoud Al Mazroa

展开 >

作者单位：

Dorset College,King George Blvd,Surrey,British Columbia,Canada

Department of Information Technology,Vignan's Foundation for Science,Technology and Research(Deemed to be University),Andhra Pradesh,India

Krupajal Computer Academy,Biju Patnaik University of Technology(BPUT),Rourkela 751002,India

Center for Artificial Intelligence,Prince Mohammad Bin Fahd University,Khobar,Saudi Arabia

NSUT,East Campus(Formerly AIACTR,Delhi 110031,India(Affiliated to Guru Gobind Singh Inderaprastha University)),Dwarka 110078,India

Department of Computer Science and Engineering Galgotias College of Engineering and Technology,Greater Noida 201310,Uttar Pradesh,India

Department of Information Systems,College of Computer and Information Sciences,Princess Nourah bint Abdulrahman University(PNU),P.O.Box 84428,Riyadh 11671,Saudi Arabia

展开 >

出版年：

2024

DOI：

10.1016/j.jnlssr.2023.12.003

安全科学与韧性(英文)

ISSN：

年,卷(期)：2024.(1)