Data Anonymization for Telco AI Use Cases

Learn about data anonymization techniques specifically tailored for telecommunications AI applications in this conference talk from The Linux Foundation. Explore state-of-the-art anonymization methods, including research works, projects, and specifications that help telecoms share data while maintaining privacy. Discover how to identify sensitive data elements unique to telecom scenarios and understand various anonymization approaches like suppression, masking, pseudonymization, generalization, swapping, perturbation, and synthetic data generation. Examine techniques ranging from classic K-Anonymity to advanced methods using NLP and Generative Adversarial Networks (GANs). See practical demonstrations of a unified anonymization tool and learn which techniques best address the dual challenges of preventing de-anonymization while preserving AI model effectiveness. Get hands-on exposure to relevant libraries and witness the real-world impact of anonymization on AI model performance in telecom applications.