{"repo":"lindsey98/Phishpedia","free":true,"listed":false,"github":"https://github.com/lindsey98/Phishpedia","clone":"git clone https://github.com/lindsey98/Phishpedia.git","description":"Official Implementation of \"Phishpedia: A Hybrid Deep Learning Based Approach to Visually Identify Phishing Webpages\" USENIX'21","language":"Python","stars":356,"topics":["cybersecurity","computer-vision","phishing-detection"],"license":"CC0-1.0","category":"machine-learning","readme_excerpt":"Phishpedia A Hybrid Deep Learning Based Approach to Visually Identify Phishing Webpages Paper • Website • Video • Dataset • Citation - This is the official implementation of \"Phishpedia: A Hybrid Deep Learning Based Approach to Visually Identify Phishing Webpages\" USENIX'21 link to paper, link to our website, link to our dataset. - Existing reference-based phishing detectors: - :x: Lack of interpretability , only give binary decision (legit or phish) - :x: Not robust against distribution shift , because the classifier is biased towards the phishing training set - :x: Lack of a large-scale phishing benchmark dataset - The contributions of our paper: - :white check mark: We propose a phishing identification system Phishpedia, which has high identification accuracy and low runtime overhead, outperforming the relevant state-of-the-art identification approaches. - :white check mark: We are the first to propose to use consistency-based method for phishing detection, in place of the traditional classification-based method. We investigate the consistency between the webpage domain and its brand intention. The detected brand intention provides a visual explanation for phishing decision. - :white check mark: Phishpedia is NOT trained on any phishing dataset , addressing the potential test-time distribution shift problem. - :white check mark: We release a 30k phishing benchmark dataset , each website is annotated with its URL, HTML, screenshot, and target brand: https://drive.google.com","default_branch":null,"files":null,"tree":[],"storefront":"/r/lindsey98","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/lindsey98/Phishpedia/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}