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

In the face of escalating global Cybersecurity threats, having an automated forewarning system that can find suspicious user profiles is paramount. It can work as a prevention technique for planned attacks or ultimate security breaches. Significant research has been established in attack prevention and detection, but has demonstrated only one or a few different sources with a short list of features. The main goals of this paper are, first, to review the previous user profiling models and analyze them to find their advantages and disadvantages; second, to provide a comprehensive overview of previous research to gather available features and data sources for user profiling; third, based on the deficiencies of the previous models, the paper proposes a new user profiling model that can cover all available sources and related features based on the cybersecurity perspective. The proposed model includes seven profiling criteria for gathering user’s information and more than 270 features to parse and generate the security profile of a user.

A Survey on User Profiling Model forAnomaly Detection in Cyberspace