2023
DOI: 10.30880/jscdm.2023.04.01.006
|View full text |Cite
|
Sign up to set email alerts
|

Feature Selection of Distributed Denial of Service (DDos) IoT Bot Attack Detection Using Machine Learning Techniques

Abstract: Distributed Denial of Service (DDoS) attacks can be made through numerous mediums, becoming one of the biggest threats to computer security. One of the most effective approaches is to develop an algorithm using Machine Learning (ML). However, the low accuracy of DDoS is because of the feature selection classifier and time-consuming detection. This research focuses on the feature selection of DDoS IoT bot attack detection using ML techniques. Two datasets from NetFlow, NF_T… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
2

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
references
References 14 publications
0
0
0
Order By: Relevance