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nlp.ipynb: This notebook pertains to the standard NLP workflow including toeknization, frequency analysis, sentiment analysis, similarity analysis, and summarization.
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ner.ipynb: This notebook pertains to deep learning based named entity recognition (NER) for automated tagging of documents.
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clustering.ipynb: This notebook pertains to non-determinstic clustering of a corpus. This is relevnat to novelty detection in unstructured log files.
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ts_anomaly_detection_prediction.ipynb: This notebook pertains to deep learning based anomaly detection and prediction for threat identication and foreasting.
| Business Case | Features |
|---|---|
| IoC Detection and Threat Prediction | Time Series Anomaly Detection and Prediction |
| High-Fidelity Multi-layer Forensic | Asynchronous Correlations |
| Faster SOC Investigations | NLP Workflow for Log Data Processing |
| Early Recognition of Zero-Day Attacks | Non-Deterministic Clustering |
| Faster Parsing of Unstructured Log Files | Automated Tagging by Named Entity Recognition (NER) |
| Faster Remediation | Recommendation Engine |