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

Network forensics involves capturing, recording and analysing network audit trails. A crucial part of network forensics is to gather evidence at the server level, proxy level and from other sources. A web proxy relays URL requests from clients to a server. Analysing web proxy logs can give unobtrusive insights to the browsing behavior of computer users and provide an overview of the Internet usage in an organisation. More importantly, in terms of network forensics, it can aid in detecting anomalous browsing behavior. This paper demonstrates the use of a self-organising map (SOM), a powerful data mining technique, in network forensics. In particular, it focuses on how a SOM can be used to analyse data gathered at the web proxy level.

Analysis of Web Proxy Logs