Feb 21, 2017 · In this paper, we present a model for detection of malicious web pages based on ensemble learning. Our major purpose of applying the idea of ...
This paper proposes a model for detection of ma- licious web pages based on ensemble learning which causes error rate reduction in classification and finally.
This study presents a classification method that combines static and dynamic data to improve the precision of locky ransomware detection and classification ...
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 ...
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The emergence of data-driven techniques, represented by machine learning (ML) algorithms, serves a promising approach to detect malicious websites. These ...
The threats according to OWASP Top 10 include SQLi, Cross-Site Scripting (XSS), XXE, etc.,In this paper, we focus on building a tool- it uses ensemble learning.
Oct 22, 2024 · In this paper we study how to detect malicious pages. Since malicious webpages are generated inconstantly, we use on line learning methods to ...
This paper presented a comparative evaluation of several machine learning algorithms and ensemble techniques for classification, to chec malicious webpages.
In this paper, we proposed an ensemble learning algorithm for discovery of malicious web pages. ... Keywords: genetic algorithms; malicious web pages; ...
To this end, we proposed a holistic approach that leverages static analysis, dynamic analysis, machine learning, and evolutionary searching and optimization to ...