Artificial Neural Network Model for Predicting Fraudulent Attacks

Autor:	Sudha, P. Divyabharathi, Y. Camry Joshya, P. Archana
Rok vydání:	2021
Předmět:	History Artificial neural network Network security business.industry Computer science Artificial neural network model Artificial intelligence business Phishing Computer Science Applications Education Sigmoid transfer function
Zdroj:	Journal of Physics: Conference Series. 1979:012016
ISSN:	1742-6596 1742-6588
DOI:	10.1088/1742-6596/1979/1/012016
Popis:	Now a days Artificial Intelligence is an emerging technology. Neural network concepts used in many applications at present situation. The usage of internet increases day by day as well as the lack of security increases day by day. Mainly phishing scams emerges highly in case of network security. In this paper Neural network concepts, how to train and test the data using Artificial neural network has been discussed which gives an brief idea about usage of Neural net concepts in field of Network security. The properties such as feed forward back propagation network form, gradient descent momentum training purpose, sigmoid transfer function, supervised learning model used to train the model for predicting fraudulent attacks.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::3dac9a3524c88c279c940e32b9a86cc1 https://doi.org/10.1088/1742-6596/1979/1/012016 Zobrazit plný text záznamu