A Classifier to Detect Profit and Non Profit Websites Upon Textual Metrics for Security Purposes
نویسندگان
چکیده
Currently, most organizations have a defense system to protect their digital communication network against cyberattacks. However, these systems deal with all traffic regardless if it is from profit or non-profit websites. This leads enforcing more security policies, which negatively affects speed. Since dangerous cyberattacks are aimed at commercial websites, because they contain critical data such as credit card numbers, better set up the priorities towards actual attacks that come study evaluated effect of textual website metrics in determining type nonprofit for purposes. Classifiers were built predict by applying machine learning techniques on dataset. The corpus used this research included and Both traditional deep applied. results showed J48 performed best terms accuracy according its outcomes cases. newly models can be significant tool organizations, will help them implement necessary policies associated both positive impact efficiency network.
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ژورنال
عنوان ژورنال: Journal of ICT Research and Applications
سال: 2022
ISSN: ['2337-5787', '2338-5499']
DOI: https://doi.org/10.5614/itbj.ict.res.appl.2022.16.1.6