LiRA Attack
Likelihood testing scenario from https://arxiv.org/pdf/2112.03570.pdf.
- class sacroml.attacks.likelihood_attack.LIRAAttack(output_dir: str = 'outputs', write_report: bool = True, n_shadow_models: int = 100, p_thresh: float = 0.05, mode: str = 'offline', fix_variance: bool = False, report_individual: bool = False)[source]
The main LiRA Attack class.
Methods
attack(target)Run a LiRA attack from a Target object and a target model.
Get parameters for this attack.
- __init__(output_dir: str = 'outputs', write_report: bool = True, n_shadow_models: int = 100, p_thresh: float = 0.05, mode: str = 'offline', fix_variance: bool = False, report_individual: bool = False) None[source]
Construct an object to execute a LiRA attack.
- Parameters:
- output_dirstr
Name of the directory where outputs are stored.
- write_reportbool
Whether to generate a JSON and PDF report.
- n_shadow_modelsint
Number of shadow models to be trained.
- p_threshfloat
Threshold to determine significance of things. For instance auc_p_value and pdif_vals.
- modestr
Attack mode: {“offline”, “offline-carlini”, “online-carlini”}
- fix_variancebool
Whether to use the global standard deviation or per record.
- report_individualbool
Whether to report metrics for each individual record.
- attack(target: Target) dict[source]
Run a LiRA attack from a Target object and a target model.
- Parameters:
- targetattacks.target.Target
target as an instance of the Target class.
- Returns:
- dict
Attack report.
- get_params() dict
Get parameters for this attack.
- Returns:
- paramsdict
Parameter names mapped to their values.