Using Clustering Algorithms to Automatically Identify Phishing Campaigns

Althobaiti, Kholoud; Wolters, Maria K.; Alsufyani, Nawal; Vaniea, Kami

doi:10.1109/access.2023.3310810

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2024

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Cited by 3 publications

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(84 reference statements)

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PD-UHD features: Phishing Detection Approach using uncooked URL, HTML content and Domain Name Features

Manjula,

Venkatesh,

Kenchamma

et al. 2024

2024 Second International Conference on Networks, Multimedia and Information Technology (NMITCON)

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PD-UHD features: Phishing Detection Approach using uncooked URL, HTML content and Domain Name Features

Manjula,

Venkatesh,

Kenchamma

et al. 2024

2024 Second International Conference on Networks, Multimedia and Information Technology (NMITCON)

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Phishing Detection in Arabic SMS Messages using Natural Language Processing

Ibrahim,

Alyousef,

Alajmi

et al. 2024

2024 Seventh International Women in Data Science Conference at Prince Sultan University (WiDS PSU)

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A review of organization-oriented phishing research

Althobaiti,

Alsufyani

2024

PeerJ Computer Science

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The increased sophistication and frequency of phishing attacks that target organizations necessitate a comprehensive cyber security strategy to handle phishing attacks from several perspectives, such as the detection of phishing and testing of users’ awareness. Through a systematic review of 163 research articles, we analyzed the organization-oriented phishing research to categorize current research and identify future opportunities. We find that a notable number of studies concentrate on phishing detection and awareness while other layers of protection are overlooked, such as the mitigation of phishing. In addition, we draw attention to shortcomings and challenges. We believe that this article will provide opportunities for future research on phishing in organizations.

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Using Clustering Algorithms to Automatically Identify Phishing Campaigns

Abstract: We thank the security company that offered the dataset that allowed us to conduct this study. We also thank Nadin Kökciyan and TULiPS lab members for their feedback and discussion on the observations.

Cited by 3 publications

References 50 publications

PD-UHD features: Phishing Detection Approach using uncooked URL, HTML content and Domain Name Features

PD-UHD features: Phishing Detection Approach using uncooked URL, HTML content and Domain Name Features

Phishing Detection in Arabic SMS Messages using Natural Language Processing

A review of organization-oriented phishing research

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