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

Mahmoud Al-Emari, Salam Radi (2022) Abnormal Transactions Detection In The Ethereum Network Using Semi-Supervised Generative Adversarial Networks. PhD thesis, Perpustakaan Hamzah Sendut.

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Abstract

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.

Item Type: Thesis (PhD)
Subjects: T Technology > T Technology (General) > T1-995 Technology(General)
Divisions: Pusat IPv6 Termaju Negara (National Advanced IPv6 Centre of Excellence NAv6) > Thesis
Depositing User: Mr Hasmizar Mansor
Date Deposited: 30 Aug 2023 01:43
Last Modified: 30 Aug 2023 01:43
URI: http://eprints.usm.my/id/eprint/59295

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