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

With the increasing number of intrusions in system and networkinfrastructures, Intrusion Detection Systems (IDS) have become an active areaof research to develop reliable and effective solutions to detect and counterthem. The use of Evolutionary Algorithms in IDS has proved its maturity overthe times. Although most of the research works have been based on the use ofgenetic algorithms in IDS, this paper presents an approach toward thegeneration of rules for the identification of anomalous connections usingevolution strategies . The emphasis is given on how the problem can be modeledinto ES primitives and how the fitness of the population can be evaluated inorder to find the local optima, therefore resulting in optimal rules that canbe used for detecting intrusions in intrusion detection systems.

An Evolution Strategy Approach toward Rule-set Generation for Network Intrusion Detection Systems (IDS)