SomaliPhishingDataset v1.0

Zenodo (CERN European Organization for Nuclear Research) 2026 Dataset Open access

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Authors: Husein Moalin Abdulahi, Mohamed Omar Mohamed, Seema B. Joshi
DOI: 10.5281/zenodo.18247187
Cited by: 0

Abstract

SomaliPhishingDataset is a Somali-language cybersecurity dataset for binary classification of digital messages as phishing (1) or ham/benign (0). The public release contains 8,684 messages collected from Whatsapp, Telegram, SMS, and Facebook/Tiktok. It includes binary labels and a rule-based annotation scheme (Rule1–Rule5) capturing common phishing tactics. All public text is PII-masked using tokens such as [URL], [PHONE], [EMAIL], and [ID]. This dataset supports reproducible benchmarking and phishing detection research for a low-resource language setting.

Fields of Study & Subjects

Spam and Phishing Detection Misinformation and Its Impacts Hate Speech and Cyberbullying Detection

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
14 January 2026
Language
SO
Document type
Dataset