- class PercentilePrivacy(percentile=10, gamma=0.01, data_kinds: List[str] | None = None)[source]¶
Implementation of “largest percentile to share” privacy preserving policy.
Shokri and Shmatikov, Privacy-preserving deep learning, CCS ‘15
percentile (int, optional) – Only abs diff greater than this percentile is updated. Allowed range 0..100. Defaults to 10.
gamma (float, optional) – The upper limit to truncate abs values of weight diff. Defaults to 0.01. Any weight diff with abs<gamma will become 0.
data_kinds – kinds of DXO to filter
- process_dxo(dxo: DXO, shareable: Shareable, fl_ctx: FLContext) None | DXO [source]¶
Compute the percentile on the abs delta_W.
Only share the params where absolute delta_W greater than the percentile value
dxo – information from client
shareable – that the dxo belongs to
fl_ctx – context provided by workflow
Returns: filtered dxo