Anonymeter by Anonos is a comprehensive synthetic data privacy assessment tool designed to evaluate the robustness of synthetic data against re-identification attacks. It simplifies the adoption of synthetic data and helps organizations comply with anonymization requirements. Anonymeter evaluates key indicators of factual anonymization for synthetic data, assisting data controllers in assessing the acceptability of residual re-identification risks and determining if a dataset is anonymous. It is user-friendly for privacy engineers and compliance teams, requiring basic data analysis skills for result interpretation. Anonymeter integrates easily into synthetic data generation and governance pipelines, promoting transparency and community contributions through its open-source and modular design. It supports large-scale synthetic data evaluations and produces reports summarizing privacy risks and recommendations for mitigation. Anonymeter aligns with GDPR Recital 26 regarding re-identification risks in anonymized datasets.
