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) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
RemusNeo_FYPReport.pdf Restricted Access | 3.9 MB | Adobe PDF | View/Open |
Page view(s)
180
Updated on May 7, 2025
Download(s)
11
Updated on May 7, 2025
Google ScholarTM
Check
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.