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 cognitive radio it is of prime importance that the presence of PrimaryUsers (PU) is detected correctly at each of the time. In order to do so thehelp from all present Secondary Users (SU) is taken and such a taken is knownas co-operative spectrum sensing. Ideally it is assumed that all the secondaryusers give the correct result to the control center. But there are certainconditions under which the secondary users deliberately forward wrong result tothe control center so as to degrade the performance of the cognitive network.In this paper we study the different techniques for detecting the malicioususers or outliers. We take into consideration practical environmental conditionsuch that the received signal of the secondary users is made to undergo fadingand noise is also introduced in the signal. We further go on to examine each ofthe outlier detector techniques and find out the most suitable at variousinstants.

Malicious User Detection in Spectrum Sensing for WRAN Using Different Outliers Detection Techniques