Apr 10, 2019 · In this paper, we proposed an ensemble learning algorithm for discovery of malicious web pages. The goal is to provide more learning chance to ...
An ensemble algorithm for discovery of malicious web pages
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In this algorithm a weight is assigned to a weak classifier and GA chooses the best set of committee members of weak classifiers to make an optimal ensemble.
Page 3. An ensemble algorithm for discovery of malicious web pages. 205. JavaScript codes, features based on URL and host and, etc.) of web pages without the.
Request PDF | On Jan 1, 2019, Hedieh Sajedi published An ensemble algorithm for discovery of malicious web pages | Find, read and cite all the research you ...
May 31, 2024 · This work proposed a stacking-based ensemble classifier to perform multi-class classification of malicious URLs on larger URL datasets.
This paper compares the prediction accuracy of several machine learning classification algorithms and ensemble techniques.
This paper aims to classify URLs and web pages into legitimate and malicious sites to alert users and allow safer browsing through the internet.
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Nov 25, 2022 · In this paper, we propose an ensemble machine learning-based malicious URL detection method for predicting malicious code distribution. There ...
Ensemble voting approaches improve the classifier's robustness, which helps determine if a suspected program in system memory is malicious.
Oct 13, 2020 · An ensemble interpretable framework is explored for automatic and efficient malicious code detection. Based on the knowledge graph of malware.