Cloud Computing Environment: An Effective New Intrusion Detection System

Rife acceptance of Cloud Computing has made it bull’s eye for the hackers. Intrusion detection System (IDS) plays a vibrant role for it. Researchers have done marvelous works on the development of a competence IDS. But there are many challenges still exists with IDS. One of the biggest concerns is that the computational complexity and false alarms of the IDS escalates with the increase in the number of features or attributes of the dataset. Hence, the concept of Feature Selection (FS) contributes an all-important role for the buildout of an efficacious IDS. New FS algorithm is put forward which is the modified Firefly Algorithm in which Decision Tree (DT) classifier is used as the classification function. We have used the hybrid classifier which is the combination of neural network and DT. We have used CSE CIC IDS 2018 dataset and simulated dataset for performance assessment. Our examination pragmatic that the performance of proposed architecture is better than the state-of-the-art algorithms.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-05
DOI
https://doi.org/10.5281/zenodo.15597743
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Cloud Computing Environment: An Effective New Intrusion Detection System

Zenodo (CERN European Organization for Nuclear Research)
Network Security and Intrusion Detection
article

Cloud Computing Environment: An Effective New Intrusion Detection System

article en

Abstract

Rife acceptance of Cloud Computing has made it bull’s eye for the hackers. Intrusion detection System (IDS) plays a vibrant role for it. Researchers have done marvelous works on the development of a competence IDS. But there are many challenges still exists with IDS. One of the biggest concerns is that the computational complexity and false alarms of the IDS escalates with the increase in the number of features or attributes of the dataset. Hence, the concept of Feature Selection (FS) contributes an all-important role for the buildout of an efficacious IDS. New FS algorithm is put forward which is the modified Firefly Algorithm in which Decision Tree (DT) classifier is used as the classification function. We have used the hybrid classifier which is the combination of neural network and DT. We have used CSE CIC IDS 2018 dataset and simulated dataset for performance assessment. Our examination pragmatic that the performance of proposed architecture is better than the state-of-the-art algorithms.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 52%
Network Security and Intrusion Detection
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Cloud Computing Environment: An Effective New Intrusion Detection System · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS