Standardize naming for target outputs and attack signals across MIA attacks
- 主要語言
- Python
- 星號
- 23
- 分支
- 28
- 平均合併
- 4 天 12 小時
- 30 天內合併 PR
- 5
描述
Different MIA implementations currently use different names for similar values. Examples include:
- base: logits_target
- attack_p: attack_signal and audit_signal
- loss_trajectory: target
- LiRA and MS-LiRA: taget_model_logitsm, target_signals, shadow_models_signals, and sample_target_signals
Use the same naming pattern across all similar MIA attacks.
The names should make it clear whether a variable contains the model’s original output or a signal calculated from that output.
For example, use `target_outputs` and `shadow_outputs` or `target_model_outputs` and `shadow_model_outputs` for original model outputs.
It might be better with `outputs` than `logits`, because LeakPro also supports regression and forecasting models, which do not necessarily produce logits.
貢獻指南
研究方向
Locate the base, attack_p, loss_trajectory, LiRA, and MS-LiRA implementations and search for the listed target, shadow, logits, signal, and audit variable names. Standardize equivalent names so original model outputs are distinct from calculated signals, while supporting regression and forecasting outputs; verify that all affected attacks still work consistently.
由索引模型根據 Issue 內容生成。
評估
- 技術堆疊
- python
- 領域
- machine-learning, security
- Issue 類型
- 重構
- 難度
- 4/5
- 預估耗時
- 3-5 天
- 活躍度
- 活躍
- 描述清晰度
- 基本清楚
- 新手友好度
- 55/100