Meta‐analysis and systematic review for anomaly network intrusion detection systems: Detection methods, dataset, validation methodology, and challenges
Intrusion detection systems built on artificial intelligence (AI) are presented as latent
mechanisms for actively detecting fresh attacks over a complex network. The authors used a …
mechanisms for actively detecting fresh attacks over a complex network. The authors used a …
From Bytes to Insights: A Systematic Literature Review on Unraveling IDS Datasets for Enhanced Cybersecurity Understanding
A Khanan, YA Mohamed, AH Mohamed… - IEEE Access, 2024 - ieeexplore.ieee.org
In the wake of the expanding digital realm, the imperative for robust cybersecurity measures
has burgeoned significantly. This extensive investigation digs into the complicated realm of …
has burgeoned significantly. This extensive investigation digs into the complicated realm of …
[HTML][HTML] A novel IDS with a dynamic access control algorithm to detect and defend intrusion at IoT nodes
The Internet of Things (IoT) is the underlying technology that has enabled connecting daily
apparatus to the Internet and enjoying the facilities of smart services. IoT marketing is …
apparatus to the Internet and enjoying the facilities of smart services. IoT marketing is …
[HTML][HTML] Comparison between Machine Learning and Physical Models Applied to the Evaluation of Co-Seismic Landslide Hazard
JC Román-Herrera, MJ Rodríguez-Peces… - Applied Sciences, 2023 - mdpi.com
A comparative methodology between advanced statistical tools and physical-based
methods is carried out to ensure their reliability and objectivity for the evaluation of co …
methods is carried out to ensure their reliability and objectivity for the evaluation of co …
Network Intrusion Detection Based on Machine Learning Classification Algorithms: A Review
AH Younis, AM Abdulazeez - JISA (Jurnal Informatika dan Sains), 2024 - trilogi.ac.id
The worldwide internet continues to spread, presenting numerous escalating hazards with
significant potential. Existing static detection systems necessitate frequent updates to …
significant potential. Existing static detection systems necessitate frequent updates to …
[PDF][PDF] COMPARATIVE ANALYSIS OF PREDICTIVE MODELS FOR WORKLOAD SCALING IN IAAS CLOUDS: A STUDY ON MODEL EFFECTIVENESS AND …
SN POTHU, DRS KAILASAM - Journal of Theoretical and Applied …, 2023 - jatit.org
The demand for dependable workload prediction models has surged in the ever-evolving
domain of cloud computing, especially across renowned platforms such as AWS, Google …
domain of cloud computing, especially across renowned platforms such as AWS, Google …
Multilingual Text Classification Based On Deep Learning Models
L Lin - 2023 IEEE 11th Joint International Information …, 2023 - ieeexplore.ieee.org
In an era characterized by global interconnectedness, the imperative for seamless
communication across diverse languages is more pronounced than ever. The present …
communication across diverse languages is more pronounced than ever. The present …
Dynamic Access Control Algorithm to Detect and Defend Intrusion for IoT Nodes
G Han - 2023 International Conference on Computer Science …, 2023 - ieeexplore.ieee.org
The Internet of Things (IoT) is the underlying technology that connects daily devices to the
Internet and provides intelligent service facilities. These eye-catching figures make it an …
Internet and provides intelligent service facilities. These eye-catching figures make it an …
Machine Learning per Intrusion Detection in IoT: Una Recensione dello Stato dell'Arte
M ANTONUTTI - thesis.unipd.it
L'internet of things (IoT) è un campo tecnologico in rapida crescita, con applicazioni in settori
come la domotica, l'agricoltura, l'automazione industriale, la sanità e molti altri ancora …
come la domotica, l'agricoltura, l'automazione industriale, la sanità e molti altri ancora …