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Detecting email phishing, a persistent cyber threat, is essential for safeguarding against potential damages. This survey comprehensively examines a spectrum of techniques employed for phishing email detection, ranging from conventional methods to advanced approaches like machine learning and behavioral analysis. Through an evaluation of each technique's merits and limitations, including considerations such as detection accuracy and scalability, this study aims to provide a nuanced understanding of their effectiveness in mitigating phishing risks. Furthermore, the survey delves into the influence of human factors, such as user awareness training, on enhancing overall detection efficacy. By synthesizing insights from diverse research efforts, this survey offers valuable insights into the current landscape of email phishing detection, informing future research directions and guiding the implementation of robust cybersecurity measures.
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Horta et al. (Sun,) studied this question.
www.synapsesocial.com/papers/68e77b26b6db6435876ef388 — DOI: https://doi.org/10.15680/ijircce.2024.1202054
Aaron Horta
A. Rengarajan
International Journal of Innovative Research in Computer and Communication Engineering
Jain University
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