Malware Detection Using Neural Network

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

Մատենագիտական մանրամասներ
Հիմնական հեղինակներ:	Kayum, Syed Irfan, Hossain, Humaira, Tasnim, Naﬁsa, Paul, Arja, Rohan, Alim Aldin
Այլ հեղինակներ:	Mostakim, Moin
Ձևաչափ:	Թեզիս
Լեզու:	English
Հրապարակվել է:	Brac University 2021
Խորագրեր:	Convolutional Neural Network Long-Short Term Memory Network Gated Recurrent Unit secondary data Malware Threats Neural networks (Computer science)
Առցանց հասանելիություն:	http://hdl.handle.net/10361/15176

id	10361-15176
record_format	dspace
spelling	10361-151762022-01-26T10:23:17Z Malware Detection Using Neural Network Kayum, Syed Irfan Hossain, Humaira Tasnim, Naﬁsa Paul, Arja Rohan, Alim Aldin Mostakim, Moin Hossain, Muhammad Iqbal Department of Computer Science and Engineering, Brac University Convolutional Neural Network Long-Short Term Memory Network Gated Recurrent Unit secondary data Malware Threats Neural networks (Computer science) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (page 37-40). One of the great and major issues facing the Internet today is a large amount of data and ﬁles that need to be analyzed for possible malicious purposes. Malicious software also referred to as an attacker’s malware is polymorphic and metamorphic in design. It has the potential to modify their code as it spreads. Increased malware and sophisticated cyber attacks are becoming a serious issue. Unknown malware that has not been identiﬁed by security vendors is often used in these attacks, making it diﬃcult to protect terminals from infection. As of now, there is a lot of research being performed to identify and monitor malware. After acknowledgment of the deep learning area, several researchers have tried to detect malware using neural networks and deep learning methods. This paper contrasts the performance of three diﬀerent neural networking models: Convolutional Neural Networks (CNN), Long-Short Term Memory (LSTM) Network, and Gated Recurrent Unit (GRU) for malware detection. Besides, we used secondary data to gather information about malware activity. Syed Irfan Kayum Humaira Hossain Naﬁsa Tasnim Arja Paul Alim Aldin Rohan B. Computer Science 2021-10-07T09:14:14Z 2021-10-07T09:14:14Z 2021 2021-01 Thesis ID 17101272 ID 17101395 ID 17101143 ID 17301006 ID 17101202 http://hdl.handle.net/10361/15176 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. 40 Pages Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Convolutional Neural Network Long-Short Term Memory Network Gated Recurrent Unit secondary data Malware Threats Neural networks (Computer science)
spellingShingle	Convolutional Neural Network Long-Short Term Memory Network Gated Recurrent Unit secondary data Malware Threats Neural networks (Computer science) Kayum, Syed Irfan Hossain, Humaira Tasnim, Naﬁsa Paul, Arja Rohan, Alim Aldin Malware Detection Using Neural Network
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
author2	Mostakim, Moin
author_facet	Mostakim, Moin Kayum, Syed Irfan Hossain, Humaira Tasnim, Naﬁsa Paul, Arja Rohan, Alim Aldin
format	Thesis
author	Kayum, Syed Irfan Hossain, Humaira Tasnim, Naﬁsa Paul, Arja Rohan, Alim Aldin
author_sort	Kayum, Syed Irfan
title	Malware Detection Using Neural Network
title_short	Malware Detection Using Neural Network
title_full	Malware Detection Using Neural Network
title_fullStr	Malware Detection Using Neural Network
title_full_unstemmed	Malware Detection Using Neural Network
title_sort	malware detection using neural network
publisher	Brac University
publishDate	2021
url	http://hdl.handle.net/10361/15176
work_keys_str_mv	AT kayumsyedirfan malwaredetectionusingneuralnetwork AT hossainhumaira malwaredetectionusingneuralnetwork AT tasnimnafisa malwaredetectionusingneuralnetwork AT paularja malwaredetectionusingneuralnetwork AT rohanalimaldin malwaredetectionusingneuralnetwork
_version_	1814309781779775488

Malware Detection Using Neural Network

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