Titlebook: Recent Advances on Soft Computing and Data Mining; Proceedings of the S Rozaida Ghazali,Nazri Mohd Nawi,Nureize Arbaiy Conference proceedin

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財(cái)主

Volatile-Oils

概觀

頑固

Detection of Phishing Websites from URLs Using Hybrid Ensemble-Based Machine Learning Technique,forms, etc. Malicious actors often create clones of legitimate websites and then lure users to access these cloned sites so that they can capture user-sensitive information. This research proposes a hybrid ensemble-based machine-learning technique for predicting phishing websites from URLs to addres

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小淡水魚

帳單

小爭吵

Detection of Phishing Websites from URLs Using Hybrid Ensemble-Based Machine Learning Technique,el. The experimental results of the proposed model demonstrate an outstanding performance of 93.0%, 92.2%, 93.4% and 92.8% for accuracy, recall, precision and f1-score respectively on the dataset used. When compared with some existing models, the model gave an outstanding performance.

訓(xùn)誡

Conference proceedings 2024ghts into the concepts and techniques essential for maximizing the outcomes of large-scale research and data mining projects. Readers are guided through analytical thinking processes, addressing challenges in deciphering complex data systems and deriving commercial value from the data. Soft computin