Predicting Cryptocurrency Fraud Using ChaosNet: The Ethereum Manifestation
- Phishing: Although fraudsters are nothing new, individuals continue to fall victim to this tactic. A malicious hyperlink in an inbox or a fraudulent website that occasionally uncannily resembles its genuine counterpart can be used in phishing scams. A victim’s personal information, such as their internet passwords or the private keys to their crypto wallet, may be stolen using the link or website.
- Man-in-the-Middle: Man-in-the-middle assaults are a technique that con artists use to obtain personal information, much like phishing scams. To access a victim’s bitcoin wallet or private account information, a fraudster will disrupt a Wi-Fi session on a broad network instead of doing so through links. One can use a VPN to secure their data while depositing cryptocurrency to avoid this.
- Investment Scam: Investment managers who offer to help a person make significant improvements to their portfolio may be fraudsters. They will entice customers to transmit their cryptocurrencies and may even promise to increase the value of their investments by 50 times. Forbes Advisor does caution that “if you comply with their demands, kiss goodbye to your cryptocurrency.” Using this scam, the con artist probably deceives several people, takes their cryptocurrency, and then vanishes.
- Pump-and-Dump: This is a tactic used in both regular stock markets and cryptocurrency marketplaces. When a coin launches, its owners sell all their holdings, known as a pump-and-dump strategy. As a result, the price reaches an erroneous peak before dropping sharply after the initial public offering is over. False statements made about a project that cause a lot of hype can worsen the impact of these tactics.
3. Data and Methods
3.1. Dataset Description
- Avgminbetweensenttnx: Minutes between each transaction on average for the account.
- Avgminbetweenreceivedtnx: Minutes between transactions received on average for the account.
- TimeDiffbetweenfirstand_last(Mins): Minutes between the first and last transactions.
- Sent_tnx: Total volume of typical transactions sent.
- Received_tnx: Total volume of typical transactions received.
- NumberofCreated_Contracts: Total number of contract transactions created.
- UniqueReceivedFrom_Addresses: Total unique addresses from which transactions were sent to the account.
- UniqueSentTo_Addresses: Total unique addresses to which transactions were sent from the account.
- MinValSent: Lowest amount of Ether sent.
- MaxValSent: Highest amount of Ether sent.
- AvgValSent: Average amount of Ether sent over time
3.2. Methods: ChaosFeatureEXtractor + ML Classifiers
- INA—Initial Neural Activity
- EPSILON_1—Noise Intensity
- DT—Discrimination Threshold
- INITIAL_NEURAL_ACTIVITY = [0.38]
- DISCRIMINATION_THRESHOLD = [0.06]
- EPSILON = [0.29]
- INITIAL_NEURAL_ACTIVITY = [0.36]
- DISCRIMINATION_THRESHOLD = [0.06]
- EPSILON = [0.29]
- INITIAL_NEURAL_ACTIVITY = [0.039]
- DISCRIMINATION_THRESHOLD = [0.070]
- EPSILON = [0.023]
4. Practical Implementation
Data Availability Statement
Conflicts of Interest
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|Algorithm||Macro F1 Score (Training)|
|Chaos Feature Extractor + AdaBoost||0.8125910159305623|
|Chaos Feature Extractor + kNN||0.7937217353400664|
|Algorithm||Macro F1 Score (Testing)|
|Chaos Feature Extractor + AdaBoost||0.6649360740269832|
|Chaos Feature Extractor + kNN||0.7888128840520701|
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Dutta, A.; Voumik, L.C.; Ramamoorthy, A.; Ray, S.; Raihan, A. Predicting Cryptocurrency Fraud Using ChaosNet: The Ethereum Manifestation. J. Risk Financial Manag. 2023, 16, 216. https://doi.org/10.3390/jrfm16040216
Dutta A, Voumik LC, Ramamoorthy A, Ray S, Raihan A. Predicting Cryptocurrency Fraud Using ChaosNet: The Ethereum Manifestation. Journal of Risk and Financial Management. 2023; 16(4):216. https://doi.org/10.3390/jrfm16040216Chicago/Turabian Style
Dutta, Anurag, Liton Chandra Voumik, Athilingam Ramamoorthy, Samrat Ray, and Asif Raihan. 2023. "Predicting Cryptocurrency Fraud Using ChaosNet: The Ethereum Manifestation" Journal of Risk and Financial Management 16, no. 4: 216. https://doi.org/10.3390/jrfm16040216