sdcMicro (version 5.8.1)

AI_applyAnonymization: AI_applyAnonymization: Automatically apply anonymization strategy using LLM

Description

Uses an agentic loop to explore multiple anonymization strategies. The LLM proposes strategies as structured tool calls, each is evaluated with a combined utility score, and the best is selected.

Usage

AI_applyAnonymization(
  sdcObj,
  k = 3,
  verbose = TRUE,
  model = NULL,
  api_key = NULL,
  provider = c("openai", "anthropic", "custom"),
  base_url = NULL,
  confirm = TRUE,
  max_iter = 2,
  n_strategies = 3,
  weights = c(1/3, 1/3, 1/3),
  generateReport = TRUE
)

Value

Modified sdcMicroObj with the best anonymization strategy applied.

Arguments

sdcObj

An object of class sdcMicroObj.

k

Desired k-anonymity level (default 3).

verbose

If TRUE, prints progress and scores for each strategy.

model

LLM model identifier. If NULL, a default is chosen per provider.

api_key

API key. If NULL, auto-detected from environment variables.

provider

LLM provider: "openai" (default), "anthropic", or "custom" for any OpenAI-compatible endpoint.

base_url

Base URL for the API endpoint. Required when provider = "custom".

confirm

Logical; if TRUE (default) and session is interactive, shows the best strategy and asks for confirmation before applying.

max_iter

Number of refinement iterations after the initial batch (default 2).

n_strategies

Number of strategies in the initial batch (default 3).

weights

Numeric vector of length 3: weights for suppression rate, category loss, and IL1 in the utility score. Default c(1/3, 1/3, 1/3).

generateReport

If TRUE, generates internal and external reports.

Author

Matthias Templ

Examples

if (FALSE) {
if (interactive() && nzchar(Sys.getenv("OPENAI_API_KEY"))) {
  library(sdcMicro)
  data(testdata)
  sdc <- AI_createSdcObj(dat = testdata, policy = "open", confirm = FALSE)
  sdc <- AI_applyAnonymization(sdcObj = sdc, k = 3, verbose = TRUE, confirm = FALSE)
}
}