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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Spam mails act as a immense hazard to communication security as it leads to phishing or virus attacks that could harm the user accounts and the organizations by exposing confidential information.With these inferences, the present research attempted to accurately detect image spam emails which have always been a topic of great research in data security. Detection of image spam mails is divided into two separate componentscharacter segmentation and character recognition. While the former segments individual characters, the latter overcomes the issue of blocked texts and not well surveyed. The final phase of the work is a complete image spam detection system with the two proposed works built to detect spam messages. Various techniques have been proposed to tackle this setback and the principle of this paper is to evaluate and review several algorithms, talk about benchmark statistics or data, show appraisal of performance followed by potential direction for future work. KeywordsFeature extraction, character segmentation, character recognition, image spam detection, and multi-SVM.

An Intelligent System for Detecting Image Spam based on Exploration of Text Information Embedded into Images