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Auditing Crypto Currency Transactions: Anomaly Detection in Bitcoin A report submitted in partial fulfillment of the requirements for the award of the degree of B.Sc. (hons) in Computing (Data Analytics)By Paris
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Define the scope and objectives of the collective anomaly detection process.
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Collect relevant data sources such as logs, metrics, and events.
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Preprocess the data by cleaning, transforming, and normalizing it.
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Choose a suitable algorithm or approach for detecting anomalies in the data.
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Train the model using historical data to identify normal behavior patterns.
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IT security teams looking to detect unusual activities or threats in their systems.
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A collective anomaly detection is a method of identifying abnormal patterns or behaviors in a group of data points.
Entities or individuals responsible for monitoring and analyzing data for potential anomalies are required to file a collective anomaly detection.
To fill out a collective anomaly detection, one must gather relevant data, analyze it for anomalies, and report any findings according to the specified format.
The purpose of a collective anomaly detection is to identify potential irregularities or unusual patterns in data that may indicate a problem or threat.
Information such as the nature of the anomaly, its potential impact, the actions taken to investigate or address it, and any recommendations for future prevention must be reported on a collective anomaly detection.
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