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Malicious Detection PDF

9 Pages·2020·English
by  ['es']
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by ['es']| 2020| 9 pages| English

About Malicious Detection

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 benchmark deep learning architectures on different datasets. Results show it performs closer to state-of-the-art methods with less computation compared to character embedding approaches for malicious URL detection.

Detailed Information

Author:['es']
Publication Year:2020
Pages:9
Language:English
Format:PDF
Price:FREE
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