Comparative analysis using supervised learning methods in anti-money laundering of Bitcoin data
- Submitting institution
-
Bournemouth University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 332541
- Type
- E - Conference contribution
- DOI
-
10.1145/3409073.3409078
- Title of conference / published proceedings
- ACM International Conference Proceeding Series
- First page
- 11
- Volume
- 0
- Issue
- 0
- ISSN
- -
- Open access status
- -
- Month of publication
- June
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
-
- Research group(s)
-
-
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper is one of a series of papers by the authors addressing approaches to prevent illicit activities in blockchain networks. Even though the issue is crucial to the success of blockchain technology, in general, there is a lack of investigation in this field. The paper is an attempt to study and propose a new approach. It is the first step of a plan to a commercialised blockchain system by the authors. This paper led to a journal paper (DOI: 10.1007/s11063-021-10424-x ).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -