English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Steganography is the concept of embedding or hiding secret information into a cover image by maintaining the visual quality. Various algorithms are designed to classify stego images but the race still continues between Steganographer and Steganalyser. Advances in deep learning provided a solution to detect stego images. In this article, we coin a new paradigm to detect stego image as a three-step process with the following repercussions: (1) employing preprocessing step to enhance the input image, (2 feature extraction using the Mustard honey bee optimization algorithm and, thus, the extracted features will be dimensionally reduced (3) by classification using HSVGG-based CNN. Experimentation carried out on ALASKA2 data set and the results were compared.

Stego Detection: Image Steganalysis Using a Novel Hidden Stego Visual Geometry Group–Based CNN Classification