privacy homomorphism - significado y definición. Qué es privacy homomorphism
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Qué (quién) es privacy homomorphism - definición

A FORM OF ENCRYPTION THAT ALLOWS COMPUTATION ON CIPHERTEXTS
Homomorphic Encryption; Privacy homomorphism; Fully homomorphic encryption; Homomorphic computing; Homomorphic cryptography

Homomorphic encryption         
Homomorphic encryption is a form of encryption that permits users to perform computations on its encrypted data without first decrypting it. These resulting computations are left in an encrypted form which, when decrypted, result in an identical output to that produced had the operations been performed on the unencrypted data.
Topological homomorphism         
TVS homomorphism; Topological vector space homomorphism; TVS-homomorphism
In functional analysis, a topological homomorphism or simply homomorphism (if no confusion will arise) is the analog of homomorphisms for the category of topological vector spaces (TVSs).
Internet privacy         
  • US Republican senator [[Jeff Flake]] spearheaded an effort to pass legislation allowing ISPs and tech firms to sell private customer information, such as their browsing history, without consent.
PERSONAL PRIVACY CONCERNING THE STORING, REPURPOSING, PROVISION TO THIRD PARTIES, AND DISPLAYING OF INFORMATION PERTAINING TO ONESELF VIA INTERNET
Jason Fortuny Craigslist prank; Jason Fortuny prank; Internet Privacy; Online privacy; Privacy (internet); Electronic privacy; Internet privacy laws and regulations; Internet tracking; Internet privacy in Sweden; Web privacy; Privacy on the Internet; Browser privacy
Internet privacy involves the right or mandate of personal privacy concerning the storing, repurposing, provision to third parties, and displaying of information pertaining to oneself via Internet. Internet privacy is a subset of data privacy.

Wikipedia

Homomorphic encryption

Homomorphic encryption is a form of encryption that allows computations to be performed on encrypted data without first having to decrypt it. The resulting computations are left in an encrypted form which, when decrypted, result in an output that is identical to that produced had the operations been performed on the unencrypted data. Homomorphic encryption can be used for privacy-preserving outsourced storage and computation. This allows data to be encrypted and out-sourced to commercial cloud environments for processing, all while encrypted.

For sensitive data, such as health care information, homomorphic encryption can be used to enable new services by removing privacy barriers inhibiting data sharing or increase security to existing services. For example, predictive analytics in health care can be hard to apply via a third party service provider due to medical data privacy concerns, but if the predictive analytics service provider can operate on encrypted data instead, these privacy concerns are diminished. Moreover, even if the service provider's system is compromised, the data would remain secure.