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English Information

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Authors
# Name
1 Matheus Moura(matheus.moura@aluno.cefet-rj.br)
2 Lais Baroni(lais.baroni}@eic.cefet-rj.br)
3 Eduardo Ogasawara(eogasawara@ieee.org)
4 Diogo Mendonça(diogosmendonca@gmail.com)

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Reference
# Reference
1 Han, J., Pei, J., and Tong, H. (2022). Data Mining: Concepts and Techniques. Morgan Kaufmann, Cambridge, MA, 4th edition edition
2 Jalal, R. N.-U.-D., Alon, I., and Paltrinieri, A. (2021). A bibliometric review of cryptocurrencies as a financial asset. Technology Analysis and Strategic Management.
3 Kamps, J. and Kleinberg, B. (2018). To the moon: defining and detecting cryptocurrency pump-and-dumps. Crime Science, 7(1).
4 Kethineni, S. and Cao, Y. (2020). The Rise in Popularity of Cryptocurrency and Associated Criminal Activity. International Criminal Justice Review, 30(3):325 – 344.
5 Kramer, D. (2005). The Way It Is and the Way It Should Be: Liability Under §10(b) of the Exchange Act and Rule 10b-5 Thereunder for Making False and Misleading Statements as Part of a Scheme to "Pump and Dump" a Stock. University of Miami Business Law Review, 13(2):243.
6 La Morgia, M., Mei, A., Sassi, F., and Stefa, J. (2020). Pump and Dumps in the Bitcoin Era: Real Time Detection of Cryptocurrency Market Manipulations. In Proceedings - International Conference on Computer Communications and Networks, ICCCN, volume 2020-August.
7 Ogasawara, E., Salles, R., Lima, J., Baroni, L., Castro, A., Carvalho, L., Borges, H., Carvalho, D., Coutinho, R., Bezerra, E., Pacitti, E., and Porto, F. (2023). harbinger: A Unified Time Series Event Detection Framework.
8 Olteanu, M., Rossi, F., and Yger, F. (2023). Meta-survey on outlier and anomaly detection. Neurocomputing, 555.
9 Rajaei, M. J. and Mahmoud, Q. H. (2023). A Survey on Pump and Dump Detection in the Cryptocurrency Market Using Machine Learning. Future Internet, 15(8).
10 Schmitt, W. (2024). Bitcoin trading volumes surge after debut of long-awaited US ETFs. Technical report, https://www.ft.com/content/f30ece62-0f1c-492a-8ccd-63ec9730573c.
11 Shumway, R. H. and Stoffer, D. S. (2017). Time Series Analysis and Its Applications: With R Examples. Springer.
12 Steinmetz, F., von Meduna, M., Ante, L., and Fiedler, I. (2021). Ownership, uses and perceptions of cryptocurrency: Results from a population survey. Technological Forecasting and Social Change, 173:121073.
13 Takeuchi, J.-I. and Yamanishi, K. (2006). A unifying framework for detecting outliers and change points from time series. IEEE Transactions on Knowledge and Data Engineering, 18(4):482 – 492.
14 Truong, C., Oudre, L., and Vayatis, N. (2020). Selective review of offline change point detection methods. Signal Processing, 167.
15 Victor, F. and Hagemann, T. (2019). Cryptocurrency Pump and Dump Schemes: Quantification and Detection. In 2019 International Conference on Data Mining Workshops (ICDMW), pages 244–251.
16 Wursthorn, M. (2021). A Bitcoin ETF Is Here. What Does That Mean for Investors? Technical report, https://www.wsj.com/articles/a-bitcoin-etf-is-almost-here-what-does-that-mean-for-investors-11634376601.
17 Xu, J. and Livshits, B. (2019). The anatomy of a cryptocurrency pump-and-dump scheme. In Proceedings of the 28th USENIX Security Symposium, pages 1609 – 1625.