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Abnormal Transactions Detection In The Ethereum Network Using Semi-Supervised Generative Adversarial Networks

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dc.contributor.authorMahmoud Al-Emari, Salam Radi
dc.date.accessioned2023-08-30T06:40:28Z
dc.date.available2023-08-30T06:40:28Z
dc.date.issued2022-04
dc.description.abstractEthereum 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.
dc.identifier.urihttps://erepo.usm.my/handle/123456789/17466
dc.subjectAbnormal Transactions Detection In The Ethereum
dc.subjectNetwork Using Semi-Supervised Generative Adversarial Networks
dc.titleAbnormal Transactions Detection In The Ethereum Network Using Semi-Supervised Generative Adversarial Networks
dc.typeResource Types::text::thesis::doctoral thesis
dspace.entity.typePublication
oairecerif.author.affiliationUniversiti Sains Malaysia
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