IDPS-LAAD-package: Intrusion Detection Prevention System Log Autoencoder Anomaly...

In SpencerButt/IDPS-LAAD: Intrusion Detection Prevention System Log Autoencoder Anomaly Detector

Description

IDPS-LAAD is designed to read in a .csv containing the Intrusion Detection Prevention System (IDPS) cyber log. The program will allow users to select what features (variables) in the data they wish to analyze. The program will then automatically prepare the data for anomaly detection analysis with an Autoencoder Neural Network (ANN). Once the data is prepared for ANN analysis, the IDPS-LAAD can automatically generate a designed experiment to test ANN hyperparameters, and subsequently run ANNs testing each of the hyperparameters. Once the 'optimal' hyperparameters are found the the analytic will analyze the IDPS cyber data and graphically display the results as well as output a user defined top 'n' anomalous observations.

Details

Currently this package has limited functionality as a shiny gadget.

You ARE REQUIRED to first load the library:

library('IDPS.LAAD')
  

THEN, launch the gadget

IDPS_Gadget
  

Calling the following without first loading the library will return an error:

IDPS.LAAD::IDPS_Gadget()
  

Author(s)

Spencer Butt, <[e-mail]>.

Maintainer: Spencer Butt <[e-mail]>

References

• Deep Learning Book Chapter 14: Autoencoders

• Deep Learning Book Chapter 11: Practical Methodology (Hyperparameters)

See Also

h2o.deeplearning

Examples

  ## Not run: 
    # To launch the gadget, you must first load the library, then call the function:
    library('IDPS.LAAD')
    IDPS_Gadget()
  
## End(Not run)

SpencerButt/IDPS-LAAD documentation built on April 20, 2020, 8:45 p.m.