Comprehensive Review Next-Generation Intrusion Prevention System (NGIPS) Based Cyber Attacks Classification and Challenges Using Machine Learning Techniques

At present, nearly all of international interactions in commerce, economics, culture, social interaction, and government at all level involving individuals, non-governmental organizations, authorities, and governmental institutions take occur online. Cyberattacks and hazards related to technology for wireless communication have become major issues for numerous government agencies and private businesses worldwide in recent times. Today's society relies heavily on electronic technology, and protecting this data against cyberattacks is a challenging issue. The motive behind cyberattacks is to financially harm companies. Next-Generation Intrusion Prevention System (NGIPS) keeps an eye on devices and network traffic for known suspicious tasks, suspect activity by alerting security administrators about known or potential dangers, or by sending alerts to a centralized security tool, an IDS can assist speed up and automate network threat Classification and Detection. In this paper Presenting Cyber Attacks Classification using Various Machine Learning techniques with Datasets and Accuracy.

Authors

Publication Details

Journal
International Journal of Innovative Science and Research Technology (IJISRT)
Published
2024-11-07
DOI
https://doi.org/10.38124/ijisrt/ijisrt24oct1440
Citations
1
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.35
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article

Comprehensive Review Next-Generation Intrusion Prevention System (NGIPS) Based Cyber Attacks Classification and Challenges Using Machine Learning Techniques

Katikam Mahesh, Kunjam Nageswara Rao
1 citations
International Journal of Innovative Science and Research Technology (IJISRT)
Network Security and Intrusion Detection
0.35
article

Comprehensive Review Next-Generation Intrusion Prevention System (NGIPS) Based Cyber Attacks Classification and Challenges Using Machine Learning Techniques

Katikam Mahesh, Kunjam Nageswara Rao
article en
1 citations

Abstract

At present, nearly all of international interactions in commerce, economics, culture, social interaction, and government at all level involving individuals, non-governmental organizations, authorities, and governmental institutions take occur online. Cyberattacks and hazards related to technology for wireless communication have become major issues for numerous government agencies and private businesses worldwide in recent times. Today's society relies heavily on electronic technology, and protecting this data against cyberattacks is a challenging issue. The motive behind cyberattacks is to financially harm companies. Next-Generation Intrusion Prevention System (NGIPS) keeps an eye on devices and network traffic for known suspicious tasks, suspect activity by alerting security administrators about known or potential dangers, or by sending alerts to a centralized security tool, an IDS can assist speed up and automate network threat Classification and Detection. In this paper Presenting Cyber Attacks Classification using Various Machine Learning techniques with Datasets and Accuracy.

International Journal of Innovative Science and Research Technology (IJISRT)
Peace, Justice and strong institutions
Openalex Percentile: Top 37%
Network Security and Intrusion Detection
0.35
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