LLMs Enable Large-Scale Deanonymization
LLMs make large-scale deanonymization practical by extracting identity signals from text, retrieving candidates with embeddings, and using reasoning to verify matches at high precision.
LLMs make large-scale deanonymization practical by extracting identity signals from text, retrieving candidates with embeddings, and using reasoning to verify matches at high precision.
EU countries reject the Commission’s proposal to change the GDPR personal data definition, prioritizing stronger privacy protections and the EDPB’s guidance on pseudonymisation.
The EDPB adopted guidelines on pseudonymisation and a position paper on data protection and competition law, emphasizing cooperation and compliance with GDPR.
EU Court emphasized that the transmission of pseudonymized data to a data recipient will not be considered personal data if the recipient cannot re-identify the data subjects.
On November 4, 2019, the Spanish Supervisory Authority (“AEPD”), in collaboration with the European Data Protection Supervisor, published guidance on the […]
The promised benefits of data-driven marketing are at grave risk unless businesses can do a better job of protecting against […]
Personal data that has been subjected to pseudonymisation will be in scope of new data portability rules, the UK’s data […]
In August 2016, Data Protection Commissioner (?DPC?) of Ireland published guidance on the use of data anonymisation and pseudonymisation.?Guidance provides […]