An approach for preventing the indexing of hijacked journal articles in scientific databases

Hijacked journals are cloned websites that resemble the homepages of legitimate journals, whose aim is to collect processing and publication fees from unwary authors. There is a growing recognition that the recent proliferation of these scam sites poses a threat to the integrity of the scientific process. This study presents an approach intended to prevent the indexing of papers published by hijacked journals in scientific databases by using classification algorithms. We will provide an overview of the problem, define key features of hijacked journals, and present a decision tree that can be used to detect hijacked publications.