Feature Selection for Improved Phishing Detection

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Provided by: Sam Hooke
Topic: Security
Format: PDF
Phishing - a hotbed of multibillion dollar underground economy - has become an important cybersecurity problem. The centralized blacklist approach used by most web browsers usually fails to detect zero-day attacks, leaving the ordinary users vulnerable to new phishing schemes; therefore, learning machine based approaches have been implemented for phishing detection. Many existing techniques in phishing website detection seem to include as many features as can be conceived, while identifying a relevant and representative subset of features to construct an accurate classifier remains an interesting issue in this particular application of machine learning.
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