Hacking smart machines with smarter ones: How to extract meaningful data from machine learning classifiers

Autor: Angelo Spognardi, Domenico Vitali, Giuseppe Ateniese, Luigi V. Mancini, Giovanni Felici, Antonio Villani

Publikováno v: International journal of security and networks
info:cnr-pdr/source/autori:Ateniese G.; Mancini L.V.; Spognardi A.; Villani A.; Vitali D.; Felici G./titolo:Hacking smart machines with smarter ones: How to extract meaningful data from machine learning classifiers/doi:10.1504%2FIJSN.2015.071829/rivista:International journal of security and networks (Print)/anno:2015/pagina_da:137/pagina_a:150/intervallo_pagine:137–150/volume:10

Machine Learning (ML) algorithms are used to train computers to perform a variety of complex tasks and improve with experience. Computers learn how to recognize patterns, make unintended decisions, or react to a dynamic environment. Certain trained m

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7fb670401c1162470da8cd783e6aa296
http://hdl.handle.net/11573/878035