This project focuses on detecting intrusions by analyzing logs collected in real-time from log aggregation systems of web-based service providers. Since the data is unlabeled, the task requires an unsupervised anomaly detection approach based on user footprint analysis.
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This project focuses on detecting intrusions by analyzing logs collected in real-time from log aggregation systems of web-based service providers. Since the data is unlabeled, the task requires an unsupervised anomaly detection approach based on user footprint analysis.
fbghkh1999/Detecting-anomalies
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This project focuses on detecting intrusions by analyzing logs collected in real-time from log aggregation systems of web-based service providers. Since the data is unlabeled, the task requires an unsupervised anomaly detection approach based on user footprint analysis.
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