Detecting a network of hijacked journals by its archive

01/04/2021 ∙ by Anna Abalkina, et al. ∙ 0 ∙ share

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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Detecting a network of hijacked journals by its archive

Authors

Phishing Detection Using Machine Learning Techniques

A Framework for Predicting Phishing Websites using Neural Networks

Fingerprinting the Fingerprinters: Learning to Detect Browser Fingerprinting Behaviors

Data-Driven Characterization and Detection of COVID-19 Themed Malicious Websites

Proceedings of the X International Workshop on Locational Analysis and Related Problems

National Bias of International Gymnastics Judges during the 2013-2016 Olympic Cycle

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