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

As computer networks have transformed in essential tools, their security has become a crucial problem for computer systems. Detecting unusual values fromlarge volumes of information produced by network traffic has acquired huge interest in the network security area. Anomaly detection is a starting point toprevent attacks, therefore it is important for all computer systems in a network have a system of detecting anomalous events in a time near their occurrence. Detecting these events can lead network administrators to identify system failures, take preventive actions and avoid a massive damage.This work presents, first, how identify network traffic anomalies through applying parallel computing techniques and Graphical Processing Units in two algorithms, one of them a supervised classification algorithm and the other based in traffic image processing.Finally, it is proposed as a challenge to resolve the anomalies detection using an unsupervised algorithm as Deep Learning.

Secure Computer Network: Strategies and Challengers in Big Data Era