sesa 20(25): e3

Research Article

A study of user experiences and network analysis on anonymity and traceability of bitcoin transactions

Download762 downloads
  • @ARTICLE{10.4108/eai.30-4-2021.169577,
        author={M A Hannan Bin Azhar and Robert Vause Whitehead},
        title={A study of user experiences and network analysis on anonymity and traceability of bitcoin transactions},
        journal={EAI Endorsed Transactions on Security and Safety},
        volume={7},
        number={25},
        publisher={EAI},
        journal_a={SESA},
        year={2021},
        month={4},
        keywords={Bitcoin, Blockchain, Crypto-currency, Digital Currency, Privacy, Security},
        doi={10.4108/eai.30-4-2021.169577}
    }
    
  • M A Hannan Bin Azhar
    Robert Vause Whitehead
    Year: 2021
    A study of user experiences and network analysis on anonymity and traceability of bitcoin transactions
    SESA
    EAI
    DOI: 10.4108/eai.30-4-2021.169577
M A Hannan Bin Azhar1,*, Robert Vause Whitehead1
  • 1: School of Engineering, Technology and Design, Canterbury Christ Church University, UK
*Contact email: hannan.azhar@canterbury.ac.uk

Abstract

This paper investigates the anonymity of bitcoin transactions and significance of awareness of the technology by bitcoin users, alongside their experiences in tracing transactions. Bitcoin enables users to carry out transactions anonymously with the virtual currency without unveiling where the real-world source of the income has come from. These transactions may occur without revealing locations or any personal identifiable information of the person who is sending or receiving bitcoins. While there are existing surveys which test bitcoin users’ awareness of the technology, they do not focus on bitcoin users’own experience using the technology in terms of tracing transactions and use of anti-forensic tools to increase the level of anonymity. This paper reports significance of users’ opinions on traceability and anonymity of bitcoin transactions and compares users’ viewpoints collected from a survey with experimental findings observed using network analysis tools.