Steganography is the art and science of hidden (or covered) communication. In digital
steganography, the bits of images, videos, audio and text files are tweaked to represent the …

In this study, we introduce a refined approach to encrypting 32-bit color images, leveraging
the potential of four 1D chaotic maps–the Logistic map, Tent map, Chebyshev map, and …

Steganalysis is a known practice to detect hidden secrecy within covered e-media.
Researches claimed obscured detection attainability via features extraction, as for …

Information hiding in images has gained popularity. As image steganography gains
relevance, techniques for detecting hidden messages have emerged. Statistical …

Electronic commerce (E-commerce) transactions require secure communication to protect
sensitive information such as credit card numbers, personal identification, and financial data …

Counting-based secret-sharing (CBSS) is a current cybersecurity technique that provide
applicable authentication for multi-participants collaborative trust access control utilization …

Emerging technologies based on the advancements in Deep Learning (DL) induced several
alternative approaches to address intricate problems, such as analyzing images in the …

As technology advances, the steganalysis methods based on Convolutional Neural Network
(CNN) can more precisely detect steganography behavior. However, the existing CNN …

Computer vision and deep learning are essential in human authentication. It provides
answers to numerous issues faced in the real world. Moreover, it has a great potential in …

Compressing medical images to reduce their size while maintaining their clinical and
diagnostic information is crucial. Because medical images can be large and demand a lot of …