Pmaraveyias commited on
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updates readme and adds sample data

Browse files
Data/CertificateFeatures-sample.parquet ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:8a98afde36b3a5187cfb7d032783f478f8157b2c2d9c59b869f29538d0f909e8
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+ size 90600349
README.md CHANGED
@@ -11,6 +11,9 @@ tags:
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  size_categories:
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  - 10M<n<100M
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  pretty_name: Machine Identity Spectra Dataset
 
 
 
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  ---
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  # Venafi Machine Identity Spectra Dataset
@@ -22,7 +25,7 @@ This collection of data contains extracted features from 19m+ certificates disco
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  public internet between July 20 and July 26, 2023.
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  The features are a combination of X.509 certificate features, RFC5280 compliance checks,
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  and other attributes intended to be used for clustering, features analysis, and a base for supervised learning tasks (labels not included).
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- Some rows may contain nan values as well and as such could require some additional pre-processing for certain tasks.
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  Venafi is excited to engage with the data science community to increase the adoption of machine learning techniques
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  in the machine identity management and wider security domains.
@@ -32,6 +35,9 @@ The extracted features are contained in the Data folder as certificateFeatures.c
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  approximately 10GB and contains 98 extracted features for approximately 19m certificates. A description of the features
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  and expected data types is contained in the base folder as features.csv.
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  ## Clustering and PCA Example
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  To demonstrate a potential use of the data, clustering and Principal Component Analysis (PCA) were
 
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  size_categories:
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  - 10M<n<100M
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  pretty_name: Machine Identity Spectra Dataset
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+ configs:
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+ - config_name: sample_data
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+ data_files: Data/CertificateFeatures-data.parquet
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  ---
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  # Venafi Machine Identity Spectra Dataset
 
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  public internet between July 20 and July 26, 2023.
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  The features are a combination of X.509 certificate features, RFC5280 compliance checks,
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  and other attributes intended to be used for clustering, features analysis, and a base for supervised learning tasks (labels not included).
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+ Some rows may contain nan values as well and as such could require additional pre-processing for certain tasks.
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  Venafi is excited to engage with the data science community to increase the adoption of machine learning techniques
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  in the machine identity management and wider security domains.
 
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  approximately 10GB and contains 98 extracted features for approximately 19m certificates. A description of the features
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  and expected data types is contained in the base folder as features.csv.
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+ The Data folder also contains a 500k row sample of the data in parquet format. This is displayed in the Data Viewer
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+ for easy visual inspection of the dataset.
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+
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  ## Clustering and PCA Example
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  To demonstrate a potential use of the data, clustering and Principal Component Analysis (PCA) were