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Open-source pipeline enables crypto data analysis and fraud detection

By PulseAugur Editorial · [1 sources] ·

A new open-source pipeline has been developed to process cryptocurrency market data, enabling ingestion, forecasting, and fraud detection on commodity hardware. This system utilizes Apache Kafka and Apache Spark to replicate cloud-native, event-driven functionalities. The pipeline was tested using historical Gemini exchange data, comparing ARIMA and LSTM models for Bitcoin price forecasting, and Random Forest and Gradient Boosting classifiers for Ethereum fraud detection. AI

IMPACT Provides a framework for researchers and developers to build and deploy AI models for cryptocurrency market analysis and fraud detection.

RANK_REASON The item is a research paper detailing an open-source pipeline for data analysis. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Open-source pipeline enables crypto data analysis and fraud detection

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The item is a research paper detailing an open-source pipeline for data analysis. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Basil Sajid Shaikh, Melrick Mascarenhas, Nuzhat Faiz Shaikh ·

    An Open-Source, Event-Driven Pipeline for Cryptocurrency Market Data: Ingestion, Forecasting, and On-Chain Fraud Detection

    arXiv:2608.29973v1 Announce Type: new Abstract: Cryptocurrency markets generate high-frequency, multi-source data that is expensive to work with unless a team already has commercial-grade streaming and warehousing infrastructure in place. This paper describes a fully open-source …

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