Phishing Email Clustering Using Quasi-Ground-Truth Machine Learning

Datasets referenced in a conference paper (submitted) Zip files are password-protected; the password will be revealed after paper acceptance. phish_public - phishing messages, a dataframe with columns: ts_anon - timestamp from_anon - sender to_anon - recipient subject_anon -suject content_anon - message text client_ip_anon - IP of the sender matched_domains - matched known malicious domains cluster_gt - spam campaign ID (ground truth) emb - embeddings of URLs in message phish_public_teaser is the preview of the file test_public - test dataset, a dataframe with columns: msg_id - message ID, as in the original dataset: AISec_Clustering paper_cluster_id - ground-truth emb - embeddings of URLs in message siamese_embeddings - embeddings of message text