DeFedOblivio: Replication and Traceability Package

Replication and traceability package for the paper “DeFedOblivio: History-Based Committee-Governed Decentralized Federated Unlearning”. This archive contains the experimental artifacts used to support the evaluation reported in the paper, including experiment configurations, replay schedules, model architecture excerpts, dataset-partitioning code, assembled result files, plotting scripts, result-assembly utilities, membership-inference attack evaluation code, and pilot convergence analysis. The package is intended to support result traceability, figure regeneration, configuration-level reproduction, and independent reimplementation of the method described in the paper. It is not a full public release of the complete execution core. The underlying decentralized federated learning testbed includes proprietary/licensed components that cannot be redistributed. Nevertheless, the package provides the artifacts required to inspect how the reported results were configured, assembled, analyzed, and plotted. Included experiments cover full-depth unlearning and retained utility, membership-inference attack evaluation, rollback fidelity, rollback-depth sensitivity, and recalibration-availability stress tests across MNIST, CIFAR-10, and FEMNIST settings. Portions of the auxiliary code, including some formatting, plotting, result-assembly, and utility code, were drafted, enhanced, or reviewed with assistance from AI-based tools. The authors reviewed and validated the final artifacts and remain responsible for the package contents and interpretation of the results.论文《DeFedOblivio：基于历史的委员会治理去中心化联邦遗忘》的复现与可追溯性包。 本归档文件包含支撑该论文所报告评估实验的全部实验制品，涵盖实验配置、重放调度方案、模型架构节选代码、数据集分区代码、整合完成的结果文件、绘图脚本、结果组装工具、成员推理攻击（membership inference attack）评估代码，以及试点收敛分析内容。 本工具包旨在支持实验结果可追溯、图表复现、配置级复现，以及对论文所述方法的独立重新实现。本包并非完整执行核心的公开发布版本。其底层去中心化联邦学习（decentralized federated learning）测试平台包含专有/授权组件，无法进行再分发。尽管如此，本包仍提供了用于检视报告结果的配置方式、组装流程、分析过程与绘图逻辑所需的全部必要制品。 所涵盖的实验覆盖全深度遗忘与保留效用、成员推理攻击评估、回滚保真度、回滚深度敏感性，以及针对MNIST、CIFAR-10与FEMNIST数据集设置的重新校准可用性压力测试。 部分辅助代码（包括部分格式化、绘图、结果组装与工具类代码）曾借助基于人工智能的工具协助起草、优化或审阅。作者已对最终制品完成审核与验证，并对本工具包的内容与结果解读承担全部责任。