Rohit Singh Rathaur
Selva Wild, CTO
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I’m an independent AI researcher. Currently, I’m focused on building accessible Carbon Market, ML use-cases for Telecommunication sectors. Right now I am actively working as a Project Team Lead (PTL) for Thoth project under Anuket at the LFN(Linux Foundation Networking). During my Academic Exchange Program at the UiT The Arctic University of Norway I worked on my Mini Master's Thesis under Dr. Deepak Gupta from TransmuteAI Lab, Dr. Dilip from BioAI Lab, and Dr. Rakesh Sharma.
Data Anonymization for Telco AI Usecases
Data anonymization can help Telcos to share data to facilitate open innovation. Two big challenges to address while anonymizing Telco data for AI usecases are (a) fool-proof against de-anonymization (b) Not hamper the power (Ex: predictive, Classification) of the AI models. The talk we cover the following:
(a) State of art of Data Anonymization applied to Telcos, including the research works, projects and specifications.
(b) What constitutes the sensitive data (names, addresses, telco-specific fields, location-data, etc). in Telco scenarios
(c) Anonymization categories such as (Suppression, Masking, Pseudonymization, Generalization, Swapping, Perturbation and Synthetic Data Generation).
(d) Approaches/techniques ranging from classic (ex: K-Anonymity) to use of NLP to GANs (Generative Adversarial Networks).
(e) Which of the above categories and techniques are applicable to Telco Data, considering the challenges of deanonymization and model-power.
(f) Demonstration of the developed unified-anonymization tool.
The talk will also include description of the libraries that can be used, demonstration of the techniques, and showcasing of the impact of anonymization on the AI models.
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