2020
DOI: 10.3390/fi12100168
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Phishing Attacks Survey: Types, Vectors, and Technical Approaches

Abstract: Phishing attacks, which have existed for several decades and continue to be a major problem today, constitute a severe threat in the cyber world. Attackers are adopting multiple new and creative methods through which to conduct phishing attacks, which are growing rapidly. Therefore, there is a need to conduct a comprehensive review of past and current phishing approaches. In this paper, a review of the approaches used during phishing attacks is presented. This paper comprises a literature review, followed by a… Show more

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Cited by 97 publications
(37 citation statements)
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“…This led the authors in [167] to manage the use of such attack in order to test it on social robots to prove how insecure they are, as well as to highlight their lack of authentication. • Phishing attacks are still ongoing with a variety of phishing attack types [168,169] targeting robotic employees and firms with different privileges and access level. This can lead to the exposure of their robotic devices inuse and lead to their compromising and loss of control.…”
Section: • Malicious Code Injection (Mci) Attacks or Remote Codementioning
confidence: 99%
“…This led the authors in [167] to manage the use of such attack in order to test it on social robots to prove how insecure they are, as well as to highlight their lack of authentication. • Phishing attacks are still ongoing with a variety of phishing attack types [168,169] targeting robotic employees and firms with different privileges and access level. This can lead to the exposure of their robotic devices inuse and lead to their compromising and loss of control.…”
Section: • Malicious Code Injection (Mci) Attacks or Remote Codementioning
confidence: 99%
“…As mentioned above, we suggest that companies or solution developers use the dataset of users' responses to real and simulated phishing attacks to train the supervised machine learning model. They can provide the machine learning model with training data from phishing simulation results and/or logs of users' responses to real phishing emails (for example, by integrating the Risk Score module with phishing detection and prevention solutions [35,36]) that contains user's response to phishing emails (e.g. a label that identifies whether the user clicked on a phishing link) and the user's behaviour/emotion score (e.g.…”
Section: Risk Scorementioning
confidence: 99%
“…Moreover, in [10], the authors presented a review of SQL injection attacks. The next paper introduces a survey of phishing attacks [11]. The research article in [12] investigates brute force attacks which aim to find the configurations of an IoT network.…”
Section: Related Workmentioning
confidence: 99%