{"id":3933,"date":"2023-08-07T17:58:34","date_gmt":"2023-08-07T17:58:34","guid":{"rendered":"https:\/\/dailyai.com\/?p=3933"},"modified":"2023-08-07T18:08:41","modified_gmt":"2023-08-07T18:08:41","slug":"ai-powered-acoustic-attack-extracts-data-from-keystrokes-with-95-precision","status":"publish","type":"post","link":"https:\/\/dailyai.com\/fr\/2023\/08\/ai-powered-acoustic-attack-extracts-data-from-keystrokes-with-95-precision\/","title":{"rendered":"Une attaque acoustique aliment\u00e9e par l'IA extrait des donn\u00e9es des frappes de clavier avec une pr\u00e9cision de 95%"},"content":{"rendered":"

Des chercheurs des universit\u00e9s britanniques Durham University, University of Surrey et Royal Holloway University of London ont mis au point une technique innovante bas\u00e9e sur l'IA pour extraire les frappes de touches \u00e0 partir d'enregistrements acoustiques.\u00a0<\/b><\/p>\n

Les <\/span>\u00e9tude<\/span><\/a> a mis au point une technique permettant de lire les frappes sur les claviers \u00e0 l'aide d'enregistrements audio. <\/span><\/p>\n

Cette technique pourrait permettre aux pirates d'analyser les frappes au clavier en prenant le contr\u00f4le du microphone d'un appareil et en recueillant des informations personnelles telles que des mots de passe, des conversations priv\u00e9es, des messages et d'autres donn\u00e9es sensibles.\u00a0<\/span><\/p>\n

Les frappes sont enregistr\u00e9es par un microphone, puis trait\u00e9es et analys\u00e9es par un mod\u00e8le d'apprentissage automatique qui d\u00e9termine leur espacement et leur position sur le clavier.\u00a0<\/span><\/p>\n

Le mod\u00e8le peut identifier les frappes individuelles avec un taux de pr\u00e9cision choquant de 95% lorsque les frappes sont enregistr\u00e9es par le microphone d'un t\u00e9l\u00e9phone proche. La pr\u00e9cision de la pr\u00e9diction est tomb\u00e9e \u00e0 93% lorsque les enregistrements effectu\u00e9s par Zoom ont \u00e9t\u00e9 utilis\u00e9s pour entra\u00eener l'algorithme de classification des sons.\u00a0<\/span><\/p>\n

Les attaques par piratage acoustique sont devenues de plus en plus sophistiqu\u00e9es en raison de la disponibilit\u00e9 g\u00e9n\u00e9ralis\u00e9e d'appareils \u00e9quip\u00e9s de microphones capables de capter des sons de haute qualit\u00e9.\u00a0<\/span><\/p>\n

Comment fonctionne le mod\u00e8le ?<\/span><\/h2>\n

L'attaque commence par l'enregistrement des frappes sur le clavier de la cible. Ces donn\u00e9es sont cruciales pour l'entra\u00eenement de l'algorithme pr\u00e9dictif.\u00a0<\/span><\/p>\n

Cet enregistrement peut \u00eatre r\u00e9alis\u00e9 \u00e0 l'aide d'un microphone situ\u00e9 \u00e0 proximit\u00e9 ou du t\u00e9l\u00e9phone de la cible infect\u00e9 par un logiciel malveillant et ayant acc\u00e8s \u00e0 son microphone.\u00a0<\/span><\/p>\n

Par ailleurs, un participant malhonn\u00eate \u00e0 un appel Zoom pourrait \u00e9tablir une corr\u00e9lation entre les messages tap\u00e9s par la cible et leur enregistrement sonore. Il peut \u00e9galement y avoir des moyens de pirater le microphone de l'ordinateur en utilisant des logiciels malveillants ou des vuln\u00e9rabilit\u00e9s logicielles.\u00a0<\/span><\/p>\n

Les chercheurs ont recueilli des donn\u00e9es d'entra\u00eenement en appuyant 25 fois sur chacune des 36 touches d'un MacBook Pro moderne et en enregistrant le son produit par chaque pression. Des formes d'ondes et des spectrogrammes ont \u00e9t\u00e9 produits \u00e0 partir de ces enregistrements, permettant de visualiser les variations identifiables pour chaque touche.\u00a0<\/span><\/p>\n

\"Frappes
Les chercheurs ont transform\u00e9 des enregistrements audio en spectrogrammes trait\u00e9s par un mod\u00e8le d'apprentissage automatique. Source : Une attaque acoustique par canal lat\u00e9ral bas\u00e9e sur l'apprentissage profond (Deep Learning) sur les claviers<\/a>.<\/figcaption><\/figure>\n

Un traitement suppl\u00e9mentaire des donn\u00e9es a \u00e9t\u00e9 effectu\u00e9 afin d'am\u00e9liorer les signaux utilis\u00e9s pour identifier les frappes.<\/span><\/p>\n

Ces images de spectrogrammes ont \u00e9t\u00e9 utilis\u00e9es pour entra\u00eener \"CoAtNet\", un classificateur d'images qui attribue diff\u00e9rents spectrogrammes audio \u00e0 diff\u00e9rentes frappes.\u00a0<\/span><\/p>\n

Pour leurs tests, les chercheurs ont utilis\u00e9 un ordinateur portable dot\u00e9 d'un clavier similaire \u00e0 celui des nouveaux ordinateurs portables d'Apple. Les microphones et les m\u00e9thodes d'enregistrement comprenaient un iPhone 13 Mini plac\u00e9 \u00e0 17 cm de la cible, Zoom et Skype.<\/span><\/p>\n

Le classificateur CoANet a d\u00e9montr\u00e9 une pr\u00e9cision de 95% \u00e0 partir des enregistrements de smartphones et de 93% \u00e0 partir de ceux captur\u00e9s via Zoom. Ils ont \u00e9galement test\u00e9 les frappes enregistr\u00e9es via Skype, qui ont donn\u00e9 une pr\u00e9cision de 91,7%.<\/span><\/p>\n

Le document de recherche sugg\u00e8re de modifier les styles de frappe ou d'utiliser des mots de passe al\u00e9atoires pour pr\u00e9venir de telles attaques, mais c'est loin d'\u00eatre pratique.\u00a0<\/span><\/p>\n

D'autres mesures d\u00e9fensives potentielles comprennent l'utilisation d'un logiciel pour reproduire les sons de la frappe, le bruit blanc ou les filtres audio de la frappe bas\u00e9s sur un logiciel. <\/span>Cependant, l'\u00e9tude a montr\u00e9 que m\u00eame un clavier silencieux pouvait \u00eatre analys\u00e9 avec succ\u00e8s pour d\u00e9tecter les frappes.\u00a0<\/span><\/p>\n

Il s'agit l\u00e0 d'un nouvel exemple de la mani\u00e8re dont l'apprentissage automatique peut permettre \u00e0 l'Union europ\u00e9enne d'atteindre ses objectifs. des techniques de fraude sophistiqu\u00e9es<\/a>. A \u00e9tude r\u00e9cente<\/a> a constat\u00e9 que de fausses voix profondes pouvaient tromper jusqu'\u00e0 25% de personnes.\u00a0<\/span><\/p>\n

Les attaques audio pourraient viser des personnes tr\u00e8s en vue, telles que des hommes politiques ou des PDG, afin de voler des informations sensibles ou de lancer des attaques par ransomware bas\u00e9es sur des conversations vol\u00e9es.\u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"

Des chercheurs des universit\u00e9s britanniques Durham University, University of Surrey et Royal Holloway University of London ont mis au point une technique innovante bas\u00e9e sur l'IA pour extraire les frappes de clavier \u00e0 partir d'enregistrements acoustiques. L'\u00e9tude a mis au point une technique permettant de lire les frappes sur les claviers \u00e0 partir d'enregistrements audio. Cette technique pourrait permettre aux pirates d'analyser les frappes en s'emparant du microphone d'un appareil et en recueillant des informations personnelles telles que des mots de passe, des conversations priv\u00e9es, des messages et d'autres donn\u00e9es sensibles. Les frappes sont enregistr\u00e9es par un microphone, puis trait\u00e9es et analys\u00e9es par un mod\u00e8le d'apprentissage automatique qui d\u00e9termine leur espacement et leur position sur le clavier. Le mod\u00e8le peut identifier des frappes individuelles avec<\/p>","protected":false},"author":2,"featured_media":3935,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[161,283,105],"class_list":["post-3933","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-fraud","tag-hackers","tag-machine-learning"],"yoast_head":"\nAI-powered acoustic attack extracts data from keystrokes with 95% precision | DailyAI<\/title>\n<meta name=\"description\" content=\"Researchers from UK universities Durham University, University of Surrey, and Royal Holloway University of London developed an innovative AI-supported technique for extracting keystrokes from acoustic recordings.\u00a0\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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