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Phishing Detection Using Machine Learning Techniques
The Internet has become an indispensable part of our life, However, It a...
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A Framework for Predicting Phishing Websites using Neural Networks
In India many people are now dependent on online banking. This raises se...
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Fingerprinting the Fingerprinters: Learning to Detect Browser Fingerprinting Behaviors
Browser fingerprinting is an invasive and opaque stateless tracking tech...
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Data-Driven Characterization and Detection of COVID-19 Themed Malicious Websites
COVID-19 has hit hard on the global community, and organizations are wor...
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Proceedings of the X International Workshop on Locational Analysis and Related Problems
The International Workshop on Locational Analysis and Related Problems w...
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National Bias of International Gymnastics Judges during the 2013-2016 Olympic Cycle
National bias in sports judging is a well-known issue and has been obser...
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Detecting a network of hijacked journals by its archive
This study describes a method to detect hijacked journals based on the analysis of the archives of clone journals. This approach is most effective in discovering a network of hijacked journals that have the same organizer(s). Analysis of the archives of clone journals allowed to detect 62 URLs of hijacked journals. It also provided the possibility to predict two clone websites before they became operational. This study shows that most detected hijacked journals represent a network of clone journals organized by one or several fraudulent individuals. The information and content of nine legitimate journals were compromised in international and national scientometric databases.
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