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anomalyDetection

anomalyDetection implements procedures to aid in detecting network log anomalies. By combining various multivariate analytic approaches relevant to network anomaly detection, it provides cyber analysts efficient means to detect suspected anomalies requiring further evaluation.

Installation

You can install anomalyDetection two ways.

  • Using the latest released version from CRAN:
install.packages("anomalyDetection")
  • Using the latest development version from GitHub:
if (packageVersion("devtools") < 1.6) {
  install.packages("devtools")
}

devtools::install_github("koalaverse/anomalyDetection", build_vignettes = TRUE)

Learning

To get started with anomalyDetection, read the intro vignette: vignette("Introduction", package = "anomalyDetection"). This will provide a thorough introduction to the functions provided in the package.

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Version

Version

0.2.5

License

GPL (>= 2)

Issues

Pull Requests

Stars

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Maintainer

Bradley Boehmke

Last Published

March 7th, 2018

Functions in AnomalyDetection (0.2.5)

anomalyDetection

anomalyDetection: An R package for implementing augmented network log anomoly detection procedures.
inspect_block

Block Inspection
kaisers_index

Kaiser's Index of Factorial Simplicity
horns_curve

Horn's Parallel Analysis
factor_analysis

Factor Analysis with Varimax Rotation
hmat

Plot a Histogram Matrix
get_all_factors

Find All Factors
bd_row

Breakdown for Mahalanobis Distance
factor_analysis_results

Easy Access to Factor Analysis Results
principal_components

Principal Component Analysis
mahalanobis_distance

Mahalanobis Distance
tabulate_state_vector

Tabulate State Vector
security_logs

Security Log Data
principal_components_result

Easy Access to Principal Component Analysis Results
mc_adjust

Multi-Collinearity Adjustment
%>%

Pipe functions