Crates.io | openfair |
lib.rs | openfair |
version | 0.1.1 |
source | src |
created_at | 2021-07-28 10:24:05.167679 |
updated_at | 2021-07-28 10:24:05.167679 |
description | Factor Analysis of Information Risk (OpenFAIR) |
homepage | |
repository | https://github.com/marirs/openfair-rs |
max_upload_size | |
id | 428295 |
size | 85,005 |
Factor Analysis of Information Risk (OpenFAIR) is a model/method to help organizations understand the level of risk present in their IT environments.
The FAIR methodology is conceived as a way to provide meaningful measurements so that it could satisfy management's desire to make effective comparisons and well-informed decisions. FAIR has become the only international standard Value at Risk (VaR) model for cyber-security and operational risk.
FAIR is a methodology for analyzing cybersecurity risk. Here, we will refer to risk as the total dollar amount of expected loss for a given timeframe. In a general sense, FAIR methodology works by breaking risk into its individual components. These components can then be measured or estimated numerically, allowing for a quantitative calculation of risk as a whole.
The actual calculation for risk often takes the form of a Monte Carlo method.
This is based on the terms found in:
"Open FAIR" is a trademark of the Open Group.
[dependencies]
openfair = "0.1.1"
and then
use openfair::{simulate, Result};
use std::fs::read_to_string;
fn main() -> Result<()> {
let input = read_to_string("data/input.json")?;
let result = simulate(&serde_json::from_str(&input)?)?;
println!("{:#?}", result);
Ok(())
}
cargo run --example eg1 -- -i data/input.json
cargo run --example eg1 -- -i data/input.json --generate-chart
License: MIT/Apache 2.0