El estudio del aprendizaje autom\u00e1tico adversarial se centra en la interacci\u00f3n entre los sistemas de aprendizaje autom\u00e1tico y sus adversarios potencialmente da\u00f1inos. Esta especialidad ha crecido y se ha diversificado con el tiempo, gracias al trabajo de muchos investigadores. Investiga c\u00f3mo las entidades da\u00f1inas pueden aprovechar y manipular los procedimientos de aprendizaje autom\u00e1tico, a menudo con el objetivo de evitar la detecci\u00f3n o inducir una clasificaci\u00f3n err\u00f3nea. Este campo abarca una amplia gama de m\u00e9todos de ataque, desde disfrazar mensajes de spam hasta manipular sistemas de veh\u00edculos aut\u00f3nomos. Esta disciplina no s\u00f3lo se centra en identificar y comprender estas amenazas, sino tambi\u00e9n en formular y ejecutar estrategias de defensa s\u00f3lidas. Estas estrategias pueden abarcar diversas t\u00e1cticas, como contramedidas en varias fases, m\u00e9todos de identificaci\u00f3n de ruidos y m\u00e9todos para evaluar las repercusiones de los ataques. La investigaci\u00f3n y exploraci\u00f3n continuas en este \u00e1mbito son cruciales para garantizar la seguridad y fiabilidad de los sistemas de aprendizaje autom\u00e1tico.<\/p>","protected":false},"excerpt":{"rendered":"
The study of adversarial machine learning concentrates on the interplay between machine learning systems and their potentially damaging adversaries. This specialty has grown and diversified over time, thanks to the work of many researchers. It investigates how harmful entities can take advantage of and manipulate machine learning procedures, often with the goal of avoiding detection […]<\/p>\n","protected":false},"author":4,"featured_media":0,"menu_order":0,"template":"","meta":{"footnotes":""},"glossary-categories":[],"glossary-tags":[],"glossary-languages":[],"class_list":["post-4775","glossary","type-glossary","status-publish","hentry"],"post_title":"Adversarial machine learning","post_content":"The study of adversarial machine learning concentrates on the interplay between machine learning systems and their potentially damaging adversaries. This specialty has grown and diversified over time, thanks to the work of many researchers. It investigates how harmful entities can take advantage of and manipulate machine learning procedures, often with the goal of avoiding detection or inducing misclassification. This field encompasses a broad range of attack methods, from disguising spam messages to tampering with autonomous vehicle systems. Crucially, the focus of this discipline is not only on identifying and comprehending these threats, but also on formulating and executing robust defense strategies. These strategies may encompass various tactics such as multi-stage countermeasures, noise identification methods, and methods for assessing the repercussions of attacks. The continual research and exploration in this area are crucial for guaranteeing the security and dependability of machine learning systems.","_links":{"self":[{"href":"https:\/\/blog.sociamonials.com\/es\/wp-json\/wp\/v2\/glossary\/4775","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blog.sociamonials.com\/es\/wp-json\/wp\/v2\/glossary"}],"about":[{"href":"https:\/\/blog.sociamonials.com\/es\/wp-json\/wp\/v2\/types\/glossary"}],"author":[{"embeddable":true,"href":"https:\/\/blog.sociamonials.com\/es\/wp-json\/wp\/v2\/users\/4"}],"version-history":[{"count":0,"href":"https:\/\/blog.sociamonials.com\/es\/wp-json\/wp\/v2\/glossary\/4775\/revisions"}],"wp:attachment":[{"href":"https:\/\/blog.sociamonials.com\/es\/wp-json\/wp\/v2\/media?parent=4775"}],"wp:term":[{"taxonomy":"glossary-categories","embeddable":true,"href":"https:\/\/blog.sociamonials.com\/es\/wp-json\/wp\/v2\/glossary-categories?post=4775"},{"taxonomy":"glossary-tags","embeddable":true,"href":"https:\/\/blog.sociamonials.com\/es\/wp-json\/wp\/v2\/glossary-tags?post=4775"},{"taxonomy":"glossary-languages","embeddable":true,"href":"https:\/\/blog.sociamonials.com\/es\/wp-json\/wp\/v2\/glossary-languages?post=4775"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}