Malware detection in blockchain using CNN

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

Bibliografiset tiedot
Päätekijät:	Alam, Afreen, Islam, Humaira, Wamim, Sadman Arif, Ahmed, Md. Tanjim, Siddiqi, Hasnat
Muut tekijät:	Mostakim, Moin
Aineistotyyppi:	Opinnäyte
Kieli:	English
Julkaistu:	Brac University 2021
Aiheet:	Malware detection Blockchain Convolutional Neural Network Malware (Computer software)
Linkit:	http://hdl.handle.net/10361/15504

id	10361-15504
record_format	dspace
spelling	10361-155042022-01-26T10:13:12Z Malware detection in blockchain using CNN Alam, Afreen Islam, Humaira Wamim, Sadman Arif Ahmed, Md. Tanjim Siddiqi, Hasnat Mostakim, Moin Department of Computer Science and Engineering, Brac University Malware detection Blockchain Convolutional Neural Network Malware (Computer software) 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 (pages 32-35). The inherent decentralized nature and peer-to-peer system of the blockchain’s popularity has been on the rise in recent times and is being adopted in various innovative applications. This technology claims to be one of the most secure inventions due to the employment of hash functions, which makes the data stored immutable. However, security issues concerning blockchains have been highlighted in recent reports, which begs the question: is the blockchain technology as invulnerable as it once claimed to be? These reports talk about malware injections which lead to data corruption, data theft as well as third parties gaining networking power. This has become a significant worry for security in the dynamic online world. To counter such security concerns, we propose a model which combines a convolutional neural network with a blockchain in order to prevent malicious data transactions and thus malware injection within a blockchain network. This convolutional neural network detects any malware that might be present in the data before a new block is created to be a part of the blockchain. We have compared two different CNN models: the VGG-16 architecture and a customized model with fewer layers. When integrated with our blockchain model, the VGG-16 convolutional neural network architecture achieves an accuracy of 90.3% while the custom model achieves an accuracy of 88.90%. Afreen Alam Humaira Islam Sadman Arif Wamim Md. Tanjim Ahmed Hasnat Siddiqi B. Computer Science 2021-10-21T04:46:22Z 2021-10-21T04:46:22Z 2021 2021-01 Thesis ID 17301038 ID 17101045 ID 17101041 ID 17301146 ID 17301186 http://hdl.handle.net/10361/15504 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. 35 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Malware detection Blockchain Convolutional Neural Network Malware (Computer software)
spellingShingle	Malware detection Blockchain Convolutional Neural Network Malware (Computer software) Alam, Afreen Islam, Humaira Wamim, Sadman Arif Ahmed, Md. Tanjim Siddiqi, Hasnat Malware detection in blockchain using CNN
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 Alam, Afreen Islam, Humaira Wamim, Sadman Arif Ahmed, Md. Tanjim Siddiqi, Hasnat
format	Thesis
author	Alam, Afreen Islam, Humaira Wamim, Sadman Arif Ahmed, Md. Tanjim Siddiqi, Hasnat
author_sort	Alam, Afreen
title	Malware detection in blockchain using CNN
title_short	Malware detection in blockchain using CNN
title_full	Malware detection in blockchain using CNN
title_fullStr	Malware detection in blockchain using CNN
title_full_unstemmed	Malware detection in blockchain using CNN
title_sort	malware detection in blockchain using cnn
publisher	Brac University
publishDate	2021
url	http://hdl.handle.net/10361/15504
work_keys_str_mv	AT alamafreen malwaredetectioninblockchainusingcnn AT islamhumaira malwaredetectioninblockchainusingcnn AT wamimsadmanarif malwaredetectioninblockchainusingcnn AT ahmedmdtanjim malwaredetectioninblockchainusingcnn AT siddiqihasnat malwaredetectioninblockchainusingcnn
_version_	1814307929074958336

Malware detection in blockchain using CNN

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