Realistic DNA De-anonymization using Phenotypic Prediction

TL;DR

This paper enhances phenotypic prediction techniques to improve DNA de-anonymization and proposes defense methods, addressing real-world challenges in linking DNA to individuals based on traits.

Contribution

It introduces improved phenotypic prediction methods and defense strategies for DNA de-anonymization, considering real-world complexities.

Findings

Enhanced phenotypic prediction accuracy

Proposed defense mechanisms against DNA de-anonymization

Addressed real-world applicability challenges

Abstract

There are a number of vectors for attack when trying to link an individual to a certain DNA sequence. Phenotypic prediction is one such vector; linking DNA to an individual based on their traits. Current approaches are not overly effective, due to a number of real world considerations. This report will improve upon current phenotypic prediction, and suggest a number of methods for defending against such an attack.