Data for: An online minimal uncertainty drift-aware method for anomaly detection in social networking

Published: 19 August 2020| Version 1 | DOI: 10.17632/zw7knrxpy5.1
Contributors:
Hadi Sadoghi Yazdi,
emad mahmodi,
Abbas Ghaemi Bafghi

Description

Our proposed data set consist of two part: Normal ( legitimate), and malicious (Phishing) pages. each sample in data set contain 75 features

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Categories

Security, World Wide Web

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