Reference

Evaluator

evaluator-package

evaluator: Quantified Risk Assessment Toolkit

Data Import and Cleansing Functions

create_templates()

Create a directory structure for risk analysis, pre-populated with templates

derive_controls()

Derive control difficulty parameters for a given qualitative scenario

encode_scenarios()

Encode qualitative data to quantitative parameters

import_capabilities()

Import capabilities from survey spreadsheet

import_scenarios()

Import scenarios from survey spreadsheet

import_spreadsheet()

Import the scenario spreadsheet

read_qualitative_inputs()

Load qualitative inputs

read_quantitative_inputs()

Load quantitative inputs

openfair_example()

Launch OpenFAIR demonstration web application

split_sheet()

Split a sheet of the survey spreadsheet into either capabilities or threats

validate_scenarios()

Validate qualitative scenario data

Modelling Functions

OpenFAIR modelling components

compare_tef_vuln()

Calculate number of loss events which occur in a simulated period

get_mean_control_strength()

Calculate difficulty strength across multiple controls by taking the mean

openfair_example()

Launch OpenFAIR demonstration web application

openfair_tef_tc_diff_lm()

Run an OpenFAIR simulation at the TEF/TC/DIFF/LM levels

openfair_tef_tc_diff_plm_sr()

Run an OpenFAIR simulation at the TEF/TC/DIFF/PLM/SR levels

run_simulation()

Run simulations for a scenario

run_simulations()

Run simulations for a list of scenarios

sample_diff()

Calculate the difficulty presented by controls, given a function and parameters for that function

sample_lef()

Sample loss event frequency

sample_lm()

Given a number of loss events and a loss distribution, calculate losses

sample_tc()

Sample threat capabilities (TC) from a distribution function

sample_tef()

Calculate the number of simulated threat event frequencies (TEF)

sample_vuln()

Calculate the vulnerability

select_loss_opportunities()

Determine which threat events result in loss opportunities

Reporting Functions

calculate_max_losses()

Calculate maximum losses

derive_control_key()

Derive control ID to control description mappings

dollar_millions()

Format dollar amounts in terms of millions of USD

explore_scenarios()

Launch the Scenario Explorer web application

exposure_histogram()

Display a histogram of losses for a scenario

generate_event_outcomes_plot()

Display the distribution of threat events contained vs. realized across all domains

generate_heatmap()

Display a heatmap of impact by domain

generate_report()

Generate sample analysis report

get_base_fontfamily()

Select a base graphics font family

identify_outliers()

Unnest a summarized results dataframe, adding outlier information

loss_exceedance_curve()

Display the loss exceedance curve for a group of one or more scenarios

loss_scatterplot()

Display a scatterplot of loss events for a scenario

risk_dashboard()

Launch a single page summary risk dashboard

theme_evaluator()

Default ggplot theme used by all Evaluator-supplied graphics

Sample Data Set

Demonstration data set for the hypothetical MetroCare Hospital

mc_capabilities

Capabilities

mc_domain_summary

Domain-level risk summary

mc_domains

Domain mappings

mc_mappings

Qualitative to quantitative mappings

mc_qualitative_scenarios

Qualitative information security risk scenarios

mc_quantitative_scenarios

Quantified information risk scenarios

mc_scenario_summary

Scenario-level risk summary

mc_simulation_results

Simulation results

Summarization Functions

summarize_domains()

Create domain-level summary of simulation results

summarize_iterations()

Create a summary of outcomes across all scenarios

summarize_scenario() summarize_scenarios()

Create a summary of the simulation results for a single scenario

summarize_to_disk()

Create all summary files and write to disk

Tidyrisk Scenario Class Functions

as_tibble(<tidyrisk_scenario>) as.data.frame(<tidyrisk_scenario>)

Coerce the parameters of a tidyrisk_scenario to a tibble

create_tidyrisk_scenario_skeleton()

Create a skeleton tidyrisk scenario object in the current document

is_tidyrisk_scenario()

Test if the object is a tidyrisk_scenario

new_tidyrisk_scenario() tidyrisk_scenario()

Construct a quantitative scenario object

print(<tidyrisk_scenario>)

Default printing of a tidyrisk_scenario

validate_tidyrisk_scenario()

Validates that a scenario object is well formed

vec_ptype_abbr.tidyrisk_scenario()

Set an abbreviation when displaying an S3 column in a tibble

Tidyrisk Factor Class Functions

new_tidyrisk_factor() tidyrisk_factor()

Construct a tidyrisk_factor object

tidyrisk_factory()

Create a tidyrisk_factor sample function

vec_cast(<tidyrisk_factor>)

Cast a tidyrisk_factor vector to a specified type