Phishing is a major threat to the data and infrastructure of healthcare organizations and many cyberattacks utilize this socially engineered.

Currently, technology cannot reliably detect.

Verkkoin this work, we investigated the practicality and the efficiency of using machine learning for phishing detection.

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Verkkophishing is an identity theft that employs social engineering methods to get confidential data from unwary users.

A phisher frequently attempts.

Verkkoseven widely used online databases, i. e. , acm, ieee xplore, sciencedirect, scopus, springer, web of science, and wiley, were searched by.

We developed four machine.

Verkkothe slr evaluated that phone phishing, email spoofing, spear phishing, and email manipulation are the frequently used phishing techniques.

Verkkoa phishing attack can put a hospital's infrastructure at risk, which in turn risks patient privacy and/or lives.

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