anonymised

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anonymised

Personal data that have been processed so as to make it impossible to know the person with whom the data are associated. Anonymisation of data is especially important for the secondary (non-trial-relate) use of personal health data.
References in periodicals archive ?
(criticizing the concept of anonymization with respect to fairness issues).
He explained that MasterCard is working on using analytics and "data anonymization" to create a safety net that weeds out fraudulent transactions.
These virtual bazaars are housed inside the Dark Net, a series of hidden websites and forums that are only accessible with such special anonymization software as Tor.
Security technologies used to address these threats include: (1) data loss or leakage prevention or protection (DLP); (2) encryption; and (3) obfuscation, masking, anonymization, tokenization, and emerging technologies such as bit splitting and homomorphic encryption.
The evolution of Anonymization methods helps out to preserve privacy and satisfy utility criteria also.
Many of these principles, such as security, would be obvious to even the most uninitiated, while others, such as anonymization, are more nuanced and specialized.
Data labeling and anonymization: Machine learning requires large amounts of training data to be effective and has a high demand for data utility.
Mikhail Dragodanov, Head of Sector in the Cybercrime Department, CDCOC: What is clear now is that the Internet resources used are publicly available and can be used by any normal user on the Internet, which allows anonymization of the sender of these messages.
The subject of performance is the supply of professional services to ensure basic and extended support of the software of the service Anonymization for OVM (public authorities) and other obliged entities, acquired under ISRS
The software allows users to identify PII or other sensitive data across an enterprise and promotes compliance and protection through anonymization, redaction and encryption.
They invariably contain personal data of the kind that needs to be protected, so data masking measures like pseudonymization, encryption, anonymization and aggregation should be adopted, preferably using a third party tool to ease the process.
In the context of LBSs, various LPPMs, such as user anonymization (random permutation) [17], location obfuscation [18] and encryption-based mechanisms [19], are further proposed to allow users in LBSs.