Merge Embedded Novelty Detection Feature into Main #56
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This pull request introduces a new feature for novelty detection in our directory clustering system. The feature uses the Jaccard distance metric to identify data drift in clusters of directories based on file updates, enhancing our system's ability to detect potential security threats.
Key Features:
Jaccard Distance Calculation: The feature calculates the Jaccard distance between different clusters, measuring the dissimilarity between them and aiding in the identification of novel or unusual patterns.
Outlier Detection: The system can now detect outliers and significant variations in the Jaccard distances over time. These may indicate potential security threats or vulnerabilities.
Integration with Directory Clustering: The novelty detection feature is fully integrated with the existing directory clustering system. This allows for proactive monitoring of potential security threats such as ransomware attacks or exploited programs by observing changes in the structure and behavior of directory clusters.