Predicting age and gender from network telemetry: Implications for privacy and impact on policy.

ABSTRACT: The systematic monitoring of private communications through the use of information technology pervades the digital age. One result of this is the potential availability of vast amount of data tracking the characteristics of mobile network users. Such data is becoming increasingly accessible for commercial use, while the accessibility of such data raises questions about the degree to which personal information can be protected. Existing regulations may require the removal of personally-identifiable information (PII) from datasets before they can be processed, but research now suggests that powerful machine learning classification methods are capable of targeting individuals for personalized marketing purposes, even in the absence of PII. This study aims to demonstrate how machine learning m

SUBMITTER: Kuang L 

PROVIDER: S-EPMC9302812 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature