phishing website detection using von aburrous maher (5 Ergebnisse)

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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Aburrous MaherDr. Maher Aburrous is an Assistant professor at Faculty of Science and Information Technology- Zarak University since 2010. He received his BS.c in Computer Science from Kuwait University in 1989. M.Sc in CIS from Arab.

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Detecting phishing website is a complex task which requires significant expert knowledge and experience. So far, various solutions have been proposed and developed to address these problems. Most of these approaches are not able to make a decision dynamically, giving rise to a large number of false positives. This is mainly due to limitation of the previously proposed approaches. In this book, we investigate and develop the application of an intelligent fuzzy-based classification system for phishing website detection. The proposed intelligent phishing detection system employed Fuzzy Logic (FL) model with association classification mining algorithms. Different phishing experiments which cover all phishing attacks, motivations and deception behavior techniques have been conducted to cover all phishing concerns. A comparative study and analysis showed that the proposed learning approach has a higher degree of predictive and detective capability than existing models. The proposed system was developed, tested and validated by incorporating the scheme as a web based plug-ins phishing toolbar to provide an effective help for real-time phishing website detection for all internet users. 192 pp. Englisch.

Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Detecting phishing website is a complex task which requires significant expert knowledge and experience. So far, various solutions have been proposed and developed to address these problems. Most of these approaches are not able to make a decision dynamically, giving rise to a large number of false positives. This is mainly due to limitation of the previously proposed approaches. In this book, we investigate and develop the application of an intelligent fuzzy-based classification system for phishing website detection. The proposed intelligent phishing detection system employed Fuzzy Logic (FL) model with association classification mining algorithms. Different phishing experiments which cover all phishing attacks, motivations and deception behavior techniques have been conducted to cover all phishing concerns. A comparative study and analysis showed that the proposed learning approach has a higher degree of predictive and detective capability than existing models. The proposed system was developed, tested and validated by incorporating the scheme as a web based plug-ins phishing toolbar to provide an effective help for real-time phishing website detection for all internet users.Books on Demand GmbH, Überseering 33, 22297 Hamburg 192 pp. Englisch.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Detecting phishing website is a complex task which requires significant expert knowledge and experience. So far, various solutions have been proposed and developed to address these problems. Most of these approaches are not able to make a decision dynamically, giving rise to a large number of false positives. This is mainly due to limitation of the previously proposed approaches. In this book, we investigate and develop the application of an intelligent fuzzy-based classification system for phishing website detection. The proposed intelligent phishing detection system employed Fuzzy Logic (FL) model with association classification mining algorithms. Different phishing experiments which cover all phishing attacks, motivations and deception behavior techniques have been conducted to cover all phishing concerns. A comparative study and analysis showed that the proposed learning approach has a higher degree of predictive and detective capability than existing models. The proposed system was developed, tested and validated by incorporating the scheme as a web based plug-ins phishing toolbar to provide an effective help for real-time phishing website detection for all internet users.