PRISMA-package {PRISMA}

Protocol Inspection and State Machine Analysis

Description

Loads and processes huge text corpora processed with the sally toolbox (<http://www.mlsec.org/sally/>). sally acts as a very fast preprocessor which splits the text files into tokens or n-grams. These output files can then be read with the PRISMA package which applies testing-based token selection and has some replicate-aware, highly tuned non-negative matrix factorization and principal component analysis implementation which allows the processing of very big data sets even on desktop machines.

Details

Package:	PRISMA
Type:	Package
Title:	Protocol Inspection and State Machine Analysis
Version:	0.2-7
Date:	2018-05-26
Depends:	Matrix, gplots, methods, ggplot2
Suggests:	tm (>= 0.6)
Author:	Tammo Krueger, Nicole Kraemer
Maintainer:	Tammo Krueger <[e-mail]>
Description:	Loads and processes huge text corpora processed with the sally toolbox (<http://www.mlsec.org/sally/>). sally acts as a very fast preprocessor which splits the text files into tokens or n-grams. These output files can then be read with the PRISMA package which applies testing-based token selection and has some replicate-aware, highly tuned non-negative matrix factorization and principal component analysis implementation which allows the processing of very big data sets even on desktop machines.
License:	GPL (>=2.0)

Index of help topics:

PRISMA-package          Protocol Inspection and State Machine Analysis
asap                    The ASAP Data Set
corpusToPrisma          Convert tm copus to PRISMA
estimateDimension       Estimate Inner Dimension
getDuplicateData        Restores Data with Duplicates
getMatrixFactorizationLabels
                        Convert Coordinates of Matrix Factorization to
                        Labels
loadPrismaData          Load PRISMA Data Files
plot.prisma             Generics For PRISMA Objects
plot.prismaDimension    Generics For PRISMA Objects
plot.prismaMF           Generics For PRISMA Objects
prismaDuplicatePCA      Matrix Factorization Based on Replicate-Aware
                        PCA
prismaHclust            Matrix Factorization Based on Hierarchical
                        Clustering
prismaNMF               Matrix Factorization Based on Replicate-Aware
                        NMF
thesis                  The Thesis Data Set

Further information is available in the following vignettes:

PRISMA	Quick introduction (source)

Author(s)

Tammo Krueger, Nicole Kraemer

Maintainer: Tammo Krueger <[e-mail]>

References

Krueger, T., Gascon, H., Kraemer, N., Rieck, K. (2012) Learning Stateful Models for Network Honeypots 5th ACM Workshop on Artificial Intelligence and Security (AISEC 2012), accepted

Krueger, T., Kraemer, N., Rieck, K. (2011) ASAP: Automatic Semantics-Aware Analysis of Network Payloads Privacy and Security Issues in Data Mining and Machine Learning - International ECML/PKDD Workshop. Lecture Notes in Computer Science 6549, Springer. 50 - 63

Examples

# please see the vingette for examples