Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/166150
Title: Identifying malicious activities through anomaly detection in ethereum network
Authors: Neo, Remus Keng Long
Keywords: Library and information science::Cryptography
Issue Date: 2023
Publisher: Nanyang Technological University
Source: Neo, R. K. L. (2023). Identifying malicious activities through anomaly detection in ethereum network. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/166150
Project: SCSE22-0199 
Abstract: The growth in blockchain technology has also brought about the rise in number of decentralized applications (dApps). dApps are open-sourced applications that operates on a blockchain network and has numerous benefits over conventional applications that we know. A key feature of dApps is the smart contract that powers it. Users interact with smart contracts through transactions to perform functions on dApps. With the growth in popularity of dApps, the occurrences of cyber-attacks have also noticeably increased. Hence, there is a need to ensure security and data on dApps are not easily breached. This project aims to develop a method to identify malicious transactions in smart contracts through the use of block explorers to consolidate historical transactional data, together with data analysis.
URI: https://hdl.handle.net/10356/166150
Schools: School of Computer Science and Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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