{"id":4816,"date":"2022-12-01T19:24:31","date_gmt":"2022-12-02T00:24:31","guid":{"rendered":"http:\/\/skimai.com\/?p=4816"},"modified":"2024-04-29T17:27:40","modified_gmt":"2024-04-29T22:27:40","slug":"blog-que-es-un-ataque-de-ai-adversario","status":"publish","type":"post","link":"https:\/\/skimai.com\/es\/blog-what-is-an-adversarial-ai-attack\/","title":{"rendered":"\u00bfQu\u00e9 es un ataque de IA adversaria?"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_1 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">\u00cdndice<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Alternar tabla de contenidos\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewbox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewbox=\"0 0 24 24\" version=\"1.2\" baseprofile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1' ><li class='ez-toc-page-1 ez-toc-heading-level-1'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/skimai.com\/es\/blog-what-is-an-adversarial-ai-attack\/#What_is_an_Adversarial_AI_Attack\" >\u00bfQu\u00e9 es un ataque de IA adversaria?<\/a><ul class='ez-toc-list-level-2' ><li class='ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/skimai.com\/es\/blog-what-is-an-adversarial-ai-attack\/#Risks_posed_by_an_Adversarial_AI_attack\" >Riesgos de un ataque de IA adversaria<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/skimai.com\/es\/blog-what-is-an-adversarial-ai-attack\/#Examples_of_Adversarial_AI_Attacks\" >Ejemplos de ataques de IA adversaria<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/skimai.com\/es\/blog-what-is-an-adversarial-ai-attack\/#How_to_defend_against_Adversarial_AI_attacks\" >C\u00f3mo defenderse de los ataques de IA adversaria<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/skimai.com\/es\/blog-what-is-an-adversarial-ai-attack\/#Conclusion\" >Conclusi\u00f3n<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h1><span class=\"ez-toc-section\" id=\"What_is_an_Adversarial_AI_Attack\"><\/span>\u00bfQu\u00e9 es un ataque de IA adversaria?<span class=\"ez-toc-section-end\"><\/span><\/h1>\n<p>Las tecnolog\u00edas de aprendizaje profundo, como la Inteligencia Artificial (IA) y el aprendizaje autom\u00e1tico (AM), presentan una serie de ventajas comerciales para las empresas. Al mismo tiempo, un ataque adversario de IA es un reto de seguridad cada vez mayor para los sistemas modernos.<br \/>\n\u00bfQu\u00e9 es un ataque Adversarial AI? Una forma de ciberataque que \"enga\u00f1a\" a los modelos de IA con datos enga\u00f1osos. Tambi\u00e9n conocido como Adversarial ML, esta forma de ataque se ha registrado principalmente en la clasificaci\u00f3n de im\u00e1genes y la detecci\u00f3n de spam.<br \/>\nA continuaci\u00f3n, analicemos los distintos riesgos que plantea un ataque de IA Adversarial.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Risks_posed_by_an_Adversarial_AI_attack\"><\/span>Riesgos de un ataque de IA adversaria<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Seg\u00fan <a href=\"https:\/\/www.csoonline.com\/article\/3664748\/adversarial-machine-learning-explained-how-attackers-disrupt-ai-and-ml-systems.html\">Alexey Rubtsov<\/a> del Global Risk Institute, \"el aprendizaje autom\u00e1tico adversarial explota las vulnerabilidades y especificidades de los modelos de ML\". Por ejemplo, el ML adversarial puede hacer que un algoritmo de negociaci\u00f3n basado en ML tome decisiones incorrectas sobre la negociaci\u00f3n.<\/p>\n<p>\u00bfDe qu\u00e9 manera un ataque de IA Adversarial supone un riesgo para los sistemas de IA y ML? He aqu\u00ed algunas conclusiones comunes:<br \/>\n<strong>Ingenier\u00eda de redes sociales:<\/strong> En este caso, el ataque de IA \"raspa\" los perfiles de los usuarios en las plataformas de redes sociales utilizando la automatizaci\u00f3n. A continuaci\u00f3n, genera contenido autom\u00e1ticamente para \"atraer\" al perfil deseado.<\/p>\n<p><strong>Deepfakes:<\/strong> Utilizados habitualmente en fraudes bancarios, los deepfakes son actores de amenazas en l\u00ednea que pueden lograr una serie de objetivos nefastos, entre ellos:<br \/>\nChantaje y extorsi\u00f3n<br \/>\nDa\u00f1ar la credibilidad y la imagen de una persona<br \/>\nFraude documental<br \/>\nRedes sociales para el acoso individual o en grupo<\/p>\n<p><strong>Ocultaci\u00f3n de malware:<\/strong> En este caso, los autores de las amenazas aprovechan el ML para ocultar el malware dentro de tr\u00e1fico \"malicioso\" que a los usuarios normales les parece normal.<\/p>\n<p><strong>Contrase\u00f1as:<\/strong> Los ataques de IA adversaria pueden incluso analizar un gran conjunto de contrase\u00f1as y generar variaciones. En otras palabras, estos ataques hacen que el proceso de descifrado de contrase\u00f1as sea m\u00e1s \"cient\u00edfico\". Adem\u00e1s de las contrase\u00f1as, el ML permite a los actores de amenazas resolver tambi\u00e9n CAPTCHAs.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Examples_of_Adversarial_AI_Attacks\"><\/span>Ejemplos de ataques de IA adversaria<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Utilizando ejemplos de IA Adversarial, los hackers pueden simplemente dise\u00f1ar un ataque para provocar que el modelo de IA cometa un error. Por ejemplo, una versi\u00f3n corrupta de una entrada v\u00e1lida del modelo.<\/p>\n<p>He aqu\u00ed algunos ejemplos populares de m\u00e9todos utilizados en los ataques de IA Adversarial:<br \/>\n<strong>M\u00e9todo FastGradient Sign (FGSM):<\/strong> Se trata de un m\u00e9todo basado en el gradiente que puede generar ejemplos de IA Adversarial para provocar la clasificaci\u00f3n err\u00f3nea de las im\u00e1genes. Para ello, a\u00f1ade una cantidad m\u00ednima de perturbaci\u00f3n al p\u00edxel de la imagen.<\/p>\n<p><strong>Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) de memoria limitada:<\/strong> Este m\u00e9todo es otro algoritmo de optimizaci\u00f3n num\u00e9rica no lineal basado en gradientes que puede minimizar el n\u00famero de perturbaciones de la imagen. Este m\u00e9todo es extremadamente eficaz para generar ejemplos de IA Adversarial.<\/p>\n<p><strong>Ataque de Deepfool:<\/strong> Se trata de otro m\u00e9todo muy eficaz para producir ataques Adversarial AI con un alto \u00edndice de clasificaci\u00f3n err\u00f3nea y menos perturbaciones. Esta forma de ataque utiliza una t\u00e9cnica de generaci\u00f3n de muestras adversariales no dirigidas para reducir la distancia euclidiana entre las muestras originales y las perturbadas.<\/p>\n<p><strong>Ataque de mapa de saliencia basado en jacobianos (JSMA):<\/strong> En esta forma de ataque de IA adversaria, los hackers utilizan la selecci\u00f3n de caracter\u00edsticas para minimizar el n\u00famero de caracter\u00edsticas modificadas, provocando as\u00ed una clasificaci\u00f3n err\u00f3nea. Las perturbaciones planas se a\u00f1aden iterativamente a las caracter\u00edsticas en funci\u00f3n del valor de saliencia en orden decreciente.<\/p>\n<p>Estos son s\u00f3lo algunos ejemplos de IA adversaria. A continuaci\u00f3n, vamos a discutir c\u00f3mo defenderse contra los ataques de IA Adversaria.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"How_to_defend_against_Adversarial_AI_attacks\"><\/span>C\u00f3mo defenderse de los ataques de IA adversaria<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><div id=\"attachment_6027\" style=\"width: 2491px\" class=\"wp-caption aligncenter\"><img decoding=\"async\" aria-describedby=\"caption-attachment-6027\" title=\"221122 skim ai infographic 2 png 01\"  src=\"http:\/\/skimai.com\/wp-content\/uploads\/2023\/07\/221122-skim-ai-infographic-2-png-01.png\" alt=\"221122 skim ai infographic 2 png 01\" width=\"2481\" height=\"7914\" \/><p id=\"caption-attachment-6027\" class=\"wp-caption-text\">221122 skim ai infographic 2 png 01<\/p><\/div><br \/>\nPara defenderse de los ataques de IA adversaria, las organizaciones necesitan un enfoque integral de la gesti\u00f3n de ML. Esto incluye el refuerzo de todas las operaciones relacionadas con ML y la supervisi\u00f3n constante de cualquier brecha en la defensa ML.<\/p>\n<p>He aqu\u00ed lo que debe comprender una estrategia de defensa t\u00edpica contra los ataques de IA adversaria:<br \/>\nCreaci\u00f3n de una evaluaci\u00f3n de riesgos existente para cada implementaci\u00f3n de ML.<br \/>\nAsignaci\u00f3n de la propiedad adecuada de todos los contenidos relacionados con el ML y gobernanza operativa.<br \/>\nCreaci\u00f3n de nuevas pol\u00edticas de seguridad para defenderse de los ataques de IA adversaria.<\/p>\n<p>Entre los enfoques de defensa eficaces, MLOps se est\u00e1 utilizando para dise\u00f1ar, desarrollar y operar modelos de ML, junto con la prueba y validaci\u00f3n de modelos. MLOps es un conjunto de buenas pr\u00e1cticas que integra lo mejor del aprendizaje autom\u00e1tico, DevOps y la ingenier\u00eda de datos. Implementa un proceso iterativo e incremental que comprende los siguientes elementos:<br \/>\n<strong>Dise\u00f1o:<\/strong><br \/>\nIngenier\u00eda de requisitos<br \/>\nPriorizaci\u00f3n de casos de uso de ML<br \/>\nComprobar la disponibilidad de los datos<br \/>\n<strong>Desarrollo de modelos:<\/strong><br \/>\nIngenier\u00eda de datos<br \/>\nIngenier\u00eda de modelos ML<br \/>\nComprobaci\u00f3n y validaci\u00f3n de modelos<br \/>\n<strong>Operaciones:<\/strong><br \/>\nDespliegue del modelo ML<br \/>\nDesarrollo de canalizaciones CI\/CD<br \/>\nSupervisi\u00f3n operativa y activaci\u00f3n<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Conclusion\"><\/span>Conclusi\u00f3n<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Seg\u00fan la Comisi\u00f3n de Seguridad Nacional de EE.UU. <a href=\"https:\/\/science.house.gov\/imo\/media\/doc\/Schmidt%20Testimony%20Attachment.pdf\">informe<\/a> sobre Inteligencia Artificial, se est\u00e1 invirtiendo un bajo porcentaje de los fondos de investigaci\u00f3n sobre IA en la defensa de los sistemas de IA frente a ataques adversarios. La creciente adopci\u00f3n de la IA y de las tecnolog\u00edas de aprendizaje autom\u00e1tico est\u00e1 en correlaci\u00f3n con el aumento de los ataques adversarios a la IA. En efecto, los sistemas de IA y ML plantean una nueva superficie de ataque, aumentando as\u00ed los riesgos relacionados con la seguridad.<\/p>","protected":false},"excerpt":{"rendered":"<p>What is an Adversarial AI Attack? Deep learning technologies like Artificial Intelligence (AI) and machine learning (ML) present a range of business benefits to enterprises. At the same time, an adversarial AI attack is a growing security challenge for modern systems. What is an Adversarial AI attack? A form of cyberattack that \u201cfools\u201d AI models [&hellip;]<\/p>\n","protected":false},"author":1003,"featured_media":4817,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"single-custom-post-template.php","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[125],"tags":[],"class_list":["post-4816","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-enterprise-ai-blog"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>What is an Adversarial AI Attack? - Skim AI<\/title>\n<meta name=\"description\" content=\"Adversarial attacks can be very deadly to a business. Avoid them at all costs. 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