{"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":"blogue-o-que-e-um-ataque-de-ia-contraditorio","status":"publish","type":"post","link":"https:\/\/skimai.com\/pt\/blog-what-is-an-adversarial-ai-attack\/","title":{"rendered":"O que \u00e9 um ataque de IA adversarial?"},"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 o \u00edndice\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Alternar<\/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\/pt\/blog-what-is-an-adversarial-ai-attack\/#What_is_an_Adversarial_AI_Attack\" >O que \u00e9 um ataque de IA adversarial?<\/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\/pt\/blog-what-is-an-adversarial-ai-attack\/#Risks_posed_by_an_Adversarial_AI_attack\" >Riscos colocados por um ataque de IA advers\u00e1ria<\/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\/pt\/blog-what-is-an-adversarial-ai-attack\/#Examples_of_Adversarial_AI_Attacks\" >Exemplos de ataques de IA advers\u00e1ria<\/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\/pt\/blog-what-is-an-adversarial-ai-attack\/#How_to_defend_against_Adversarial_AI_attacks\" >Como se defender contra ataques de IA advers\u00e1ria<\/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\/pt\/blog-what-is-an-adversarial-ai-attack\/#Conclusion\" >Conclus\u00e3o<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h1><span class=\"ez-toc-section\" id=\"What_is_an_Adversarial_AI_Attack\"><\/span>O que \u00e9 um ataque de IA adversarial?<span class=\"ez-toc-section-end\"><\/span><\/h1>\n<p>As tecnologias de aprendizagem profunda, como a Intelig\u00eancia Artificial (IA) e a aprendizagem autom\u00e1tica (ML), apresentam uma s\u00e9rie de benef\u00edcios comerciais para as empresas. Ao mesmo tempo, um ataque de IA advers\u00e1rio \u00e9 um desafio de seguran\u00e7a crescente para os sistemas modernos.<br \/>\nO que \u00e9 um ataque de IA advers\u00e1ria? Uma forma de ciberataque que \"engana\" os modelos de IA com dados enganadores. Tamb\u00e9m conhecido como Adversarial ML, esta forma de ataque tem sido largamente registada na classifica\u00e7\u00e3o de imagens e na dete\u00e7\u00e3o de spam.<br \/>\nDe seguida, vamos discutir os v\u00e1rios riscos colocados por um ataque de IA Advers\u00e1ria.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Risks_posed_by_an_Adversarial_AI_attack\"><\/span>Riscos colocados por um ataque de IA advers\u00e1ria<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>De acordo com <a href=\"https:\/\/www.csoonline.com\/article\/3664748\/adversarial-machine-learning-explained-how-attackers-disrupt-ai-and-ml-systems.html\">Alexey Rubtsov<\/a> do Global Risk Institute, \"a aprendizagem autom\u00e1tica adversarial explora as vulnerabilidades e especificidades dos modelos de aprendizagem autom\u00e1tica\". Por exemplo, a aprendizagem autom\u00e1tica adversa pode levar um algoritmo de negocia\u00e7\u00e3o baseado em aprendizagem autom\u00e1tica a tomar decis\u00f5es incorrectas sobre a negocia\u00e7\u00e3o.<\/p>\n<p>Como \u00e9 que um ataque de IA advers\u00e1ria representa um risco para os sistemas de IA e de ML? Eis algumas conclus\u00f5es comuns:<br \/>\n<strong>Engenharia das redes sociais:<\/strong> Neste caso, o ataque de IA \"raspa\" os perfis dos utilizadores nas plataformas de redes sociais utilizando a automatiza\u00e7\u00e3o. Em seguida, gera conte\u00fado automaticamente para \"atrair\" o perfil pretendido.<\/p>\n<p><strong>Deepfakes:<\/strong> Normalmente utilizados em fraudes banc\u00e1rias, os deepfakes s\u00e3o agentes de amea\u00e7as em linha que podem atingir uma s\u00e9rie de objectivos nefastos, incluindo:<br \/>\nChantagem e extors\u00e3o<br \/>\nPrejudicar a credibilidade e a imagem de uma pessoa<br \/>\nFraude documental<br \/>\nRedes sociais para ass\u00e9dio individual ou em grupo<\/p>\n<p><strong>Oculta\u00e7\u00e3o de malware:<\/strong> Aqui, os agentes de amea\u00e7as utilizam o ML para esconder o malware no tr\u00e1fego \"malicioso\" que parece normal para os utilizadores regulares.<\/p>\n<p><strong>Palavras-passe:<\/strong> Os ataques de IA advers\u00e1ria podem at\u00e9 analisar um grande conjunto de palavras-passe e gerar varia\u00e7\u00f5es. Por outras palavras, estes ataques tornam o processo de decifra\u00e7\u00e3o de palavras-passe mais \"cient\u00edfico\". Para al\u00e9m das palavras-passe, o ML permite que os agentes de amea\u00e7as tamb\u00e9m resolvam CAPTCHAs.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Examples_of_Adversarial_AI_Attacks\"><\/span>Exemplos de ataques de IA advers\u00e1ria<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Utilizando exemplos de IA advers\u00e1ria, os piratas inform\u00e1ticos podem simplesmente conceber um ataque para fazer com que o modelo de IA cometa um erro. Por exemplo, uma vers\u00e3o corrompida de uma entrada de modelo v\u00e1lida.<\/p>\n<p>Eis alguns exemplos populares de m\u00e9todos utilizados em ataques de IA Advers\u00e1ria:<br \/>\n<strong>M\u00e9todo do sinal de gradiente r\u00e1pido (FGSM):<\/strong> Este \u00e9 um m\u00e9todo baseado em gradientes que pode gerar exemplos de IA advers\u00e1ria para causar a classifica\u00e7\u00e3o incorrecta de imagens. Para tal, adiciona uma quantidade m\u00ednima de perturba\u00e7\u00e3o ao pixel da imagem.<\/p>\n<p><strong>Mem\u00f3ria limitada Broyden-Fletcher-Goldfarb-Shanno (L-BFGS):<\/strong> Este m\u00e9todo \u00e9 outro algoritmo de otimiza\u00e7\u00e3o num\u00e9rica n\u00e3o linear baseado em gradientes que pode minimizar o n\u00famero de perturba\u00e7\u00f5es da imagem. Este m\u00e9todo \u00e9 extremamente eficaz na gera\u00e7\u00e3o de exemplos de IA Adversarial.<\/p>\n<p><strong>Ataque de Deepfool:<\/strong> Este \u00e9 outro m\u00e9todo altamente eficaz na produ\u00e7\u00e3o de ataques de IA advers\u00e1ria com uma elevada taxa de erros de classifica\u00e7\u00e3o e menos perturba\u00e7\u00f5es. Esta forma de ataque utiliza uma t\u00e9cnica de gera\u00e7\u00e3o de amostras advers\u00e1rias n\u00e3o direccionadas para reduzir a dist\u00e2ncia euclidiana entre as amostras originais e as perturbadas.<\/p>\n<p><strong>Ataque ao mapa de sali\u00eancia baseado em jacobianos (JSMA):<\/strong> Nesta forma de ataque de IA advers\u00e1ria, os hackers utilizam a sele\u00e7\u00e3o de caracter\u00edsticas para minimizar o n\u00famero de caracter\u00edsticas modificadas, causando assim erros de classifica\u00e7\u00e3o. As perturba\u00e7\u00f5es planas s\u00e3o adicionadas iterativamente \u00e0s caracter\u00edsticas com base no valor de sali\u00eancia por ordem decrescente.<\/p>\n<p>Estes s\u00e3o apenas alguns exemplos de IA Advers\u00e1ria. De seguida, vamos discutir como nos podemos defender dos ataques da IA Advers\u00e1ria.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"How_to_defend_against_Adversarial_AI_attacks\"><\/span>Como se defender contra ataques de IA advers\u00e1ria<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 infogr\u00e1fico 2 png 01\"  src=\"http:\/\/skimai.com\/wp-content\/uploads\/2023\/07\/221122-skim-ai-infographic-2-png-01.png\" alt=\"221122 skim ai infogr\u00e1fico 2 png 01\" width=\"2481\" height=\"7914\" \/><p id=\"caption-attachment-6027\" class=\"wp-caption-text\">221122 skim ai infogr\u00e1fico 2 png 01<\/p><\/div><br \/>\nPara se defenderem contra ataques de IA advers\u00e1ria, as organiza\u00e7\u00f5es precisam de uma abordagem abrangente \u00e0 gest\u00e3o de ML. Isto inclui o refor\u00e7o de todas as opera\u00e7\u00f5es relacionadas com o ML e a monitoriza\u00e7\u00e3o constante de quaisquer viola\u00e7\u00f5es na defesa do ML.<\/p>\n<p>Eis o que deve incluir uma estrat\u00e9gia de defesa t\u00edpica contra ataques de IA advers\u00e1ria:<br \/>\nCriar uma avalia\u00e7\u00e3o de risco existente para cada implementa\u00e7\u00e3o de ML.<br \/>\nAtribui\u00e7\u00e3o da propriedade adequada de todo o conte\u00fado relacionado com o ML e governa\u00e7\u00e3o operacional.<br \/>\nCria\u00e7\u00e3o de novas pol\u00edticas de seguran\u00e7a para a defesa contra ataques de IA advers\u00e1ria.<\/p>\n<p>Entre as abordagens de defesa eficazes, o MLOps est\u00e1 a ser utilizado para conceber, desenvolver e operar modelos de ML, juntamente com o teste e a valida\u00e7\u00e3o de modelos. O MLOps \u00e9 um conjunto de pr\u00e1ticas recomendadas que integra o melhor do aprendizado de m\u00e1quina, DevOps e engenharia de dados. Implementa um processo iterativo e incremental que inclui os seguintes elementos:<br \/>\n<strong>Conce\u00e7\u00e3o:<\/strong><br \/>\nEngenharia de requisitos<br \/>\nPrioriza\u00e7\u00e3o de casos de utiliza\u00e7\u00e3o de ML<br \/>\nVerifica\u00e7\u00e3o da disponibilidade dos dados<br \/>\n<strong>Desenvolvimento de modelos:<\/strong><br \/>\nEngenharia de dados<br \/>\nEngenharia de modelos ML<br \/>\nTeste e valida\u00e7\u00e3o de modelos<br \/>\n<strong>Opera\u00e7\u00f5es:<\/strong><br \/>\nImplementa\u00e7\u00e3o do modelo ML<br \/>\nDesenvolvimento de pipeline CI\/CD<br \/>\nMonitoriza\u00e7\u00e3o operacional e acionamento<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Conclusion\"><\/span>Conclus\u00e3o<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>De acordo com a Comiss\u00e3o de Seguran\u00e7a Nacional dos EUA <a href=\"https:\/\/science.house.gov\/imo\/media\/doc\/Schmidt%20Testimony%20Attachment.pdf\">relat\u00f3rio<\/a> sobre Intelig\u00eancia Artificial, uma baixa percentagem dos fundos de investiga\u00e7\u00e3o em IA est\u00e1 a ser investida na defesa dos sistemas de IA contra ataques advers\u00e1rios. A crescente ado\u00e7\u00e3o de tecnologias de IA e de aprendizagem autom\u00e1tica est\u00e1 correlacionada com o aumento dos ataques de IA advers\u00e1ria. Efetivamente, os sistemas de IA e de aprendizagem autom\u00e1tica representam uma nova superf\u00edcie de ataque, aumentando assim os riscos relacionados com a seguran\u00e7a.<\/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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