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

Recent years witnessed a surge in network traffic due to the emergence of newonline services, causing periodic saturation and complexity problems.Additionally, the growing number of IoT devices further compounds the problem.Software Defined Network (SDN) is a new architecture which offers innovativeadvantages that help to reduce saturation problems. Despite its benefits, SDNsnot only can be affected by traditional attacks but also introduce new securitychallenges. In this context, Distributed Denial of Service (DDoS) is one of themost important attacks that can damage an SDN network's normal operation.Furthermore, if these attacks are executed using botnets, they can usethousands of compromised devices to disrupt critical online services. Thispaper proposes a framework for detecting DDoS attacks generated by a group ofbotnets in an SDN network. The framework is implemented using open-source toolssuch as Mininet and OpenDaylight and tested in a centralized network topologyusing BYOB and SNORT. The results demonstrate real-time attack identificationby implementing an intrusion detection mechanism in the victim client. Ourproposed solution offers quick and effective detection of DDoS attacks in SDNnetworks. The framework can successfully differentiate the type of attack withhigh accuracy in a short time

Detection of Distributed Denial of Service Attacks Carried Out by Botnets in Software-Defined Networks