KnowPhish introduces a novel approach to enhance phishing detection by combining logo-based and text-based methods. The study demonstrates significant improvements in effectiveness and efficiency compared to state-of-the-art baselines. The field study on local webpages validates the robustness and accuracy of KnowPhish and KPD in real-world scenarios.
Phishing attacks pose a significant threat to individuals and businesses, necessitating advanced automated detection methods. Existing RBPDs face limitations due to manual brand knowledge bases, leading to false negatives. KnowPhish addresses these issues by automating knowledge collection and introducing a multimodal approach for improved detection.
The study highlights the importance of incorporating text-based analysis alongside traditional logo-based methods for comprehensive phishing detection. By leveraging a large-scale brand knowledge base, KnowPhish significantly enhances the performance of RBPDs, particularly in identifying logo-less phishing webpages.
In a field study on local web traffic, KnowPhish outperforms commercial detectors like URLScan, demonstrating its effectiveness in real-world settings. The results showcase the potential of multimodal approaches like KPD for accurate and efficient phishing detection across diverse contexts.
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