Malicious URLs Detection Using Decision Tree Classifiers and Majority Voting Technique

Malicious URLs Detection Using Decision Tree Classifiers and Majority Voting Technique

Researchers all over the world have provided significant and effective solutions to detect malicious URLs. Still due to the ever changing nature of cyberattacks, there are many open issues. In this paper, we have provided an effective hybrid methodology with new features to deal with this problem. T...

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Bibliographic Details
Main Authors: Patil Dharmaraj R., Patil J. B.
Format: Article
Language:English
Published: Sciendo 2018-03-01
Series:Cybernetics and Information Technologies
Subjects:
static and dynamic analysis
feature extraction
decision tree learning
malicious urls
web security
Online Access:https://doi.org/10.2478/cait-2018-0002

Internet

https://doi.org/10.2478/cait-2018-0002

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