Comparison of Adaboost with MultiBoosting for Phishing Website Detection
نویسندگان
چکیده
منابع مشابه
Phishing website detection using weighted feature line embedding
The aim of phishing is tracing the users' s private information without their permission by designing a new website which mimics the trusted website. The specialists of information technology do not agree on a unique definition for the discriminative features that characterizes the phishing websites. Therefore, the number of reliable training samples in phishing detection problems is limited. M...
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This article is devoted to a new iterative construction of hierarchical classifiers in SimpleCLI for the detection of phishing websites. Our new construction of hierarchical systems creates ensembles of ensembles in SimpleCLI by iteratively linking a top-level ensemble to another middle-level ensemble instead of a base classifier so that the top-level ensemble can generate a large multilevel sy...
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Phishing website creators and anti-phishing defenders are in an arms race. Cloning a website is fairly easy and can be automated by any junior programmer. Attempting to recognize numerous phishing links posted in the wild e.g. on social media sites or in email is a constant game of escalation. Automated phishing website detection systems need both speed and accuracy to win. We present a new met...
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-Website phishing is one of the crucial research topics for the internet community due to the massive number of online daily transactions. The process of predicting the phishing activity for a website is a typical classification problem in data mining where different website’s features such as URL length, prefix and suffix, IP address, etc., are used to discover concealed correlations (knowledg...
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ژورنال
عنوان ژورنال: Procedia Computer Science
سال: 2020
ISSN: 1877-0509
DOI: 10.1016/j.procs.2020.02.251