Nadezhda Purtova's scientific contributions

Citations

... They point out that there is a basic contradiction between the GDPR on the one hand, which implies an acceptable residual risk of identification compatible with the anonymous status of data, with interpretations by national supervisory authorities as well as the European Data Protection Board on the other, which consider that no remaining risk of identification is acceptable for data to qualify as anonymous. Purtova has provided a similar analysis of the uncertainties surrounding the concept of identification and identifiability as critical boundary concepts of data protection law [87]. Another open thread of legal discussion concerns the question whether the scope of personal data protection should be extended to ML models, such as DL networks trained on personal data [88]. ...