Abnormal Transactions Detection In The Ethereum Network Using Semi-Supervised Generative Adversarial Networks
Ethereum network is a blockchain platform that allows users to use cryptocurrency transactions, create, and deploy decentralized applications using smart contracts. Several abnormal transactions came to light due to the existing attacks that targeted Ethereum, for instance, the Ethereum DAO attack,...
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my-usm-ep.592952023-08-30T01:43:57Z Abnormal Transactions Detection In The Ethereum Network Using Semi-Supervised Generative Adversarial Networks 2022-04 Mahmoud Al-Emari, Salam Radi T1-995 Technology(General) Ethereum network is a blockchain platform that allows users to use cryptocurrency transactions, create, and deploy decentralized applications using smart contracts. Several abnormal transactions came to light due to the existing attacks that targeted Ethereum, for instance, the Ethereum DAO attack, and malicious users might exploit and compromise the vulnerabilities in smart contracts, to steal amount of cryptocurrency or working for their own objectives through abnormal transactions. Therefore, detecting abnormal transactions initiated from these malicious users, implicated in fraudulent activities as well as attribution is excessively complex. However, malicious activities using cryptocurrency transactions, through pseudo-anonymous accounts for sending and receiving ransom payment, consolidation of funds heaped up under diverse identities; thus, controlling and detecting these abnormal transactions is a fundamental pre-requisite to ensure the high level of security in Ethereum network. 2022-04 Thesis http://eprints.usm.my/59295/ http://eprints.usm.my/59295/1/24%20Pages%20from%20SALAM%20RADI%20MAHMOUD%20AL-E%27MARI%20-%20TESIS.pdf application/pdf en public phd doctoral Perpustakaan Hamzah Sendut Pusat Ipv6 Termaju Negara |
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English |
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T1-995 Technology(General) |
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T1-995 Technology(General) Mahmoud Al-Emari, Salam Radi Abnormal Transactions Detection In The Ethereum Network Using Semi-Supervised Generative Adversarial Networks |
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Ethereum network is a blockchain platform that allows users to use cryptocurrency transactions, create, and deploy decentralized applications using smart contracts. Several abnormal transactions came to light due to the existing attacks that targeted Ethereum, for instance, the Ethereum DAO attack, and malicious users might exploit and compromise the vulnerabilities in smart contracts, to steal amount of cryptocurrency or working for their own objectives through abnormal transactions. Therefore, detecting abnormal transactions initiated from these malicious users, implicated in fraudulent activities as well as attribution is excessively complex. However, malicious activities using cryptocurrency transactions, through pseudo-anonymous accounts for sending and receiving ransom payment, consolidation of funds heaped up under diverse identities; thus, controlling and detecting these abnormal transactions is a fundamental pre-requisite to ensure the high level of security in Ethereum network. |
format |
Thesis |
qualification_name |
Doctor of Philosophy (PhD.) |
qualification_level |
Doctorate |
author |
Mahmoud Al-Emari, Salam Radi |
author_facet |
Mahmoud Al-Emari, Salam Radi |
author_sort |
Mahmoud Al-Emari, Salam Radi |
title |
Abnormal Transactions Detection In The Ethereum Network Using Semi-Supervised Generative Adversarial Networks |
title_short |
Abnormal Transactions Detection In The Ethereum Network Using Semi-Supervised Generative Adversarial Networks |
title_full |
Abnormal Transactions Detection In The Ethereum Network Using Semi-Supervised Generative Adversarial Networks |
title_fullStr |
Abnormal Transactions Detection In The Ethereum Network Using Semi-Supervised Generative Adversarial Networks |
title_full_unstemmed |
Abnormal Transactions Detection In The Ethereum Network Using Semi-Supervised Generative Adversarial Networks |
title_sort |
abnormal transactions detection in the ethereum network using semi-supervised generative adversarial networks |
granting_institution |
Perpustakaan Hamzah Sendut |
granting_department |
Pusat Ipv6 Termaju Negara |
publishDate |
2022 |
url |
http://eprints.usm.my/59295/1/24%20Pages%20from%20SALAM%20RADI%20MAHMOUD%20AL-E%27MARI%20-%20TESIS.pdf |
_version_ |
1776101281877721088 |