A Systematic Review on Phishing Detection: A Perspective Beyond a High Accuracy in Phishing Detection

Phishing is one of the cyberattacks most feared by users who use transactional services over the Internet, although there are a lot of studies focused on detecting phishing attacks showing high accuracy, those have problems acting with the effectiveness required to prevent people to fall into these attacks in the early stages. In this article, a state-of-the-art overview of phishing detection is shown using a systematic literature review methodology for studies addressed between 2016 and 2022, such as other survey papers between 2020 and 2022, focused on the different detection stages, information sources, phishing characterization, and different methods used in the literature. Found that 83% of applications works selected are focused on the mitigation stage, where the methodologies act in reactive ways using statics features that provides high accuracy but turn the models fail through time. Finally, conclusions will be presented to highlight the importance of using brand information and mixing different methods to improve stage detection and assure durability in the detection model. The article’s contribution is focused on establishing another perspective that encourages future research and future related works to consider their models beyond a high accuracy and start thinking about how these models can to provide effective solutions that could be integrated into production environments to protect the users.