{"id":35504,"date":"2019-10-31T22:04:42","date_gmt":"2019-10-31T19:04:42","guid":{"rendered":"https:\/\/prohoster.info\/blog\/google-otkryl-sistemu-dlya-analiza-naborov-dannyh-bez-narusheniya-konfedentsialnosti\/"},"modified":"2019-10-31T22:04:42","modified_gmt":"2019-10-31T19:04:42","slug":"google-otkryl-sistemu-dlya-analiza-naborov-dannyh-bez-narusheniya-konfedentsialnosti","status":"publish","type":"post","link":"https:\/\/prohoster.info\/es\/blog\/news\/google-otkryl-sistemu-dlya-analiza-naborov-dannyh-bez-narusheniya-konfedentsialnosti","title":{"rendered":"Google ha abierto un sistema para analizar conjuntos de datos sin violar la privacidad.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

La empresa Google ha presentado<\/a><\/noindex> protocolo criptogr\u00e1fico de computaci\u00f3n multiparte secreta Private Join and Compute<\/a><\/noindex>, que permite el an\u00e1lisis y c\u00e1lculos sobre conjuntos de datos cifrados de m\u00faltiples participantes, manteniendo la confidencialidad de los datos de cada participante (cada participante no tiene la capacidad de obtener informaci\u00f3n sobre los datos de otros, pero puede realizar c\u00e1lculos generalizados sin descifrar). El c\u00f3digo de implementaci\u00f3n del protocolo es abierto<\/a><\/noindex> bajo la licencia Apache 2.0.<\/p>\n

Private Join and Compute permite transferir un conjunto privado de registros a un tercero, que podr\u00e1 realizar su an\u00e1lisis y evaluar de manera general las diferencias con su propio conjunto, pero no puede conocer los valores de registros espec\u00edficos. Por ejemplo, es posible obtener informaci\u00f3n como el n\u00famero de identificadores coincidentes con su conjunto y las sumas de los valores de los registros con identificadores coincidentes dentro de un conjunto de datos cifrado. Sin embargo, no es posible conocer cu\u00e1les son exactamente los valores e identificadores presentes en el conjunto.<\/p>\n

El protocolo Private Join and Compute, tambi\u00e9n conocido como Private Intersection-Sum, se basa<\/a><\/noindex> se basa en una combinaci\u00f3n del protocolo de transferencia aleatoria olvidable<\/a><\/noindex> (Random Oblivious Transfer), cifrado de filtros de Bloom<\/a><\/noindex> y en doble enmascaramiento Poliga \u2014 Hellman<\/a><\/noindex>.<\/p>\n

El sistema propuesto puede ser \u00fatil, por ejemplo, cuando una instituci\u00f3n m\u00e9dica tiene informaci\u00f3n sobre el estado de salud de los pacientes, mientras que otra cuenta con datos sobre la prescripci\u00f3n de un nuevo medicamento preventivo. El protocolo \u00abPrivate Join and Compute\u00bb permite combinar conjuntos de datos cifrados sin revelar informaci\u00f3n y obtener estad\u00edsticas generales que ayudan a entender si el medicamento prescrito reduce la morbidez o no. Otro ejemplo es el uso de la base de datos de accidentes de la polic\u00eda de tr\u00e1fico junto con la base de datos de la implementaci\u00f3n de dispositivos de seguridad avanzados en autom\u00f3viles, que permite evaluar si la aparici\u00f3n de estos dispositivos afecta la cantidad de accidentes.<\/p>\n

Otro ejemplo es cuando, bas\u00e1ndose en la base de empleados de una empresa y los datos de compras de otra, se puede calcular cu\u00e1ntos empleados de la primera empresa realizaron compras en la segunda y por cu\u00e1nto dinero. En el contexto de las redes publicitarias, se pueden realizar c\u00e1lculos similares para evaluar la efectividad de las campa\u00f1as publicitarias, operando con listas de usuarios a los que se les mostr\u00f3 la publicidad (o que hicieron clic en el enlace) y que realizaron compras en la tienda en l\u00ednea.<\/p>\n

<\/a><\/noindex><\/p>\n

Fuente: opennet.ru<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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