Data anonymization irreversibly transforms data in a privacy-preserving way. The outcome is still clear data that can be of use for the CSPs and external users, but with a lower accuracy (and, thus, a lower disclosure risk) than the original data. Data anonymization is performed once at the storage stage; after that, any queries on the data (search, retrieval, calculations) are transparent to CLARUS and the CSP, even though they may result in approximate results.

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Data encryption is a method to protect data in a secure and reversible way. The scheme requires a secret key that is used both to encrypt and to decrypt data: it is a symmetric-key encryption scheme.

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Data splitting makes a local partition of the sensitive data and separately stores data fragments in different CSPs, in a way that each individual fragment does not cause privacy risks; data fragments are stored in the clear without any modification

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Homomorphic encryption is used to store data in a secure way that allows performing certain computations directly on the encrypted data. The encryption is reversible. The security of the scheme is based on the hardness of the mathematical problem that is needed to recover the original data.

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Searchable encryption is used to store data in a secure way that allows performing queries on the encrypted data. The encryption is reversible. The security of the scheme is based on the hardness of the mathematical problem that is needed to recover the original data.

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