Hybrid features-based prediction for novel phish websites

• Main Authors: Zuhair, H., Salleh, M., Selama, A.
• Format: Article
• Language: English
• Published: Penerbit UTM Press 2016
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/74338/1/MazleenaSalleh2016_HybridFeaturesBasedPrediction.pdf; http://eprints.utm.my/id/eprint/74338/; https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006427558&doi=10.11113%2fjt.v78.10026&partnerID=40&md5=e7f8f4998b87c2c6a53d3ead32965da0

Phishers frequently craft novel deceptions on their websites and circumvent existing anti-phishing techniques for insecure intrusions, users’ digital identity theft, and then illegal profits. This raises the needs to incorporate new features for detecting novel phish websites and optimizing the exis...