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Deep Learning for Malicious URL Detection by es is a document available to read on EtoBox.

1) Malicious URLs are commonly used to spread unsolicited content like spam, malware, and phishing scams. Existing malicious URL detection methods like blacklisting are ineffective against variants or new malicious URLs. 2) The paper proposes DeepURLDetect (DUD), a deep learning model that uses character-level embedding to capture sequential patterns in URLs for malicious URL detection. This avoids manual feature engineering and generalizes better than existing methods. 3) DUD is evaluated against benchmar

Author

es

Language

EN