Learning a deep neural network for predicting phishing website

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019.

Manylion Llyfryddiaeth
Prif Awduron:	Das, Robat, Hossain, Md. Mukhter, Islam, Shariful, Siddiki, Abujarr
Awduron Eraill:	Alam, Md. Ashraful
Fformat:	Traethawd Ymchwil
Iaith:	English
Cyhoeddwyd:	Brac University 2019
Pynciau:	Neural network Phishing attack Scheming Machine learning LSTM Neural networks (Computer science) Machine learning.
Mynediad Ar-lein:	http://hdl.handle.net/10361/12395

id	10361-12395
record_format	dspace
spelling	10361-123952022-01-26T10:20:03Z Learning a deep neural network for predicting phishing website Das, Robat Hossain, Md. Mukhter Islam, Shariful Siddiki, Abujarr Alam, Md. Ashraful Department of Computer Science and Engineering, Brac University Neural network Phishing attack Scheming Machine learning LSTM Neural networks (Computer science) Machine learning. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019. Cataloged from PDF version of thesis. Includes bibliographical references (pages 32-33). In recent years, we have seen a huge paradigm shift in business because of the fast development of the Web. For this reason, consumers change their tendency from customary shopping to the electronic business. In the time of electronic and versatile trade, huge quantities of money related exchanges are directed online on regular schedule, which created opportunities for new potential scheming chances. By utilizing the unknown structure of theWeb, attackers set out new procedures like phishing, to fool people with the utilization of false sites to gather their delicate data. It gather datas such as account IDs, usernames, passwords, credit card information and so on. In spite of the fact that organizations and software companies uses methodologies such as heuristics, visual and machine learning to prevent phishing attacks, still these can't keep the majority of the phishing assaults. In this paper, we evaluate the model by using LSTM technique by comparing it with previous studies and we will try to nd out the best features in LSTM. Robat Das Md. Mukhter Hossain Shariful Islam Abujarr Siddiki B. Computer Science and Engineering 2019-07-18T06:10:45Z 2019-07-18T06:10:45Z 2019 2019-05 Thesis ID 13101130 ID 14301131 ID 13201005 ID 13321060 http://hdl.handle.net/10361/12395 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 33 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Neural network Phishing attack Scheming Machine learning LSTM Neural networks (Computer science) Machine learning.
spellingShingle	Neural network Phishing attack Scheming Machine learning LSTM Neural networks (Computer science) Machine learning. Das, Robat Hossain, Md. Mukhter Islam, Shariful Siddiki, Abujarr Learning a deep neural network for predicting phishing website
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019.
author2	Alam, Md. Ashraful
author_facet	Alam, Md. Ashraful Das, Robat Hossain, Md. Mukhter Islam, Shariful Siddiki, Abujarr
format	Thesis
author	Das, Robat Hossain, Md. Mukhter Islam, Shariful Siddiki, Abujarr
author_sort	Das, Robat
title	Learning a deep neural network for predicting phishing website
title_short	Learning a deep neural network for predicting phishing website
title_full	Learning a deep neural network for predicting phishing website
title_fullStr	Learning a deep neural network for predicting phishing website
title_full_unstemmed	Learning a deep neural network for predicting phishing website
title_sort	learning a deep neural network for predicting phishing website
publisher	Brac University
publishDate	2019
url	http://hdl.handle.net/10361/12395
work_keys_str_mv	AT dasrobat learningadeepneuralnetworkforpredictingphishingwebsite AT hossainmdmukhter learningadeepneuralnetworkforpredictingphishingwebsite AT islamshariful learningadeepneuralnetworkforpredictingphishingwebsite AT siddikiabujarr learningadeepneuralnetworkforpredictingphishingwebsite
_version_	1814309192935145472

Learning a deep neural network for predicting phishing website

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