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Publication Type : Conference Paper
Publisher : Advances in Distributed Computing and Machine Learning, Singapore, 2021.
Source : Advances in Distributed Computing and Machine Learning, Springer Singapore, Singapore (2021)
ISBN : 9789811542183
Campus : Bengaluru
School : School of Engineering
Department : Computer Science
Year : 2021
Abstract : Phishing is most popular in cybercrimes where a malicious individual or a group of individuals who scam users. The aim of identifying any phished website is to help the users/customers with more secure usage of online transactional websites. The research work focuses on the neural network concept which is implemented to identify phished websites. This concept is proved by multilayer perceptron (MLP)-based classification for 48 features. For result assessment, MLP is compared with other machine learning methods such as random forest, support vector machine (SVM), logistic regression and detected to have a higher accuracy of 96.80%.
Cite this Research Publication : A. Dev and Jain, V., “Identifying Phished Website Using Multilayer Perceptron”, in Advances in Distributed Computing and Machine Learning, Singapore, 2021.