International Journal of Emerging Technology and Advanced Engineering · 2021 · 32 citations · 10 references
Spam FilteringAbuse DetectionPhishing UrlsMachine LearningData ScienceData MiningAttack TechniqueEngineeringThreat DetectionSupervised Learning AlgorithmsKnowledge DiscoveryIntrusion Detection SystemPhishingText Mining
The attack technique targeting end-users through phishing URLs is very dangerous nowadays. With this technique, attackers could steal user data or take control of the system, etc. Therefore, early detecting phishing URLs is essential. In this paper, we propose a method to detect phishing URLs based on supervised learning algorithms and abnormal behaviors from URLs. Finally, based on the research results, we build a framework for detecting phishing URLs through endusers. The novelty and advantage of our proposed method are that abnormal behaviors are extracted based on URLs which are monitored and collected directly from attack campaigns instead of using inefficient old datasets. Keywords— phishing URLs; detecting phishing URLs; abnormal behaviors of phishing URLs; Machine learning
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Machine Learning and Deep Learning Methods for Cybersecurity
Yang Xin, Lingshuang Kong, Zhi Liu et al. · IEEE Access · 2018 · 1.1K citations · Full text