{"id":8622,"date":"2023-07-21T10:53:53","date_gmt":"2023-07-21T10:53:53","guid":{"rendered":"https:\/\/komorebi.ai\/?page_id=8622"},"modified":"2023-09-21T14:15:13","modified_gmt":"2023-09-21T14:15:13","slug":"adversarial-machine-learning-bayesian-perspectives","status":"publish","type":"page","link":"https:\/\/komorebi.ai\/en\/adversarial-machine-learning-bayesian-perspectives\/","title":{"rendered":"Adversarial Machine Learning: Bayesian Perspectives"},"content":{"rendered":"
\n\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t

Adversarial Machine Learning: Bayesian Perspectives<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

Journal of the American Statistical Association<\/span>, 2023<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t

Abstract<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

Adversarial Machine Learning (AML) is a growing field focused on defending Machine Learning (ML) systems from security threats where adversaries manipulate input data to deceive these systems.\u00a0<\/span><\/p>

While most AML work relies on game-theoretic modeling of the conflict between an ML system and its adversary, this approach makes unrealistic assumptions about each party’s knowledge of the other’s intentions and uncertainties.\u00a0\u00a0<\/span><\/p>

This<\/span> paper<\/span> proposes<\/span> a Bayesian approach <\/b>that<\/span> allows<\/span> for better modeling of uncertainties<\/b> regarding an opponent’s beliefs and interests, offering a more realistic and robust defensive method for ML-based systems.\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t
<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t
<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t
<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t
<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t

A Bayesian approach to enhance defense against security threats in Machine Learning systems, applicable across cybersecurity, unsupervised learning and natural language processing.<\/p><\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

\n\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t
<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t
<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t
<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t
<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t
<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t
<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t
<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t

Where does it apply?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

The Bayesian approach to Adversarial Machine Learning is applicable in enhancing <\/span>cybersecurity <\/b>by protecting machine learning systems from attacks.\u00a0 It can be used in unsupervised learning to improve methods such as clustering, and in natural language processing to create robust language models.\u00a0\u00a0<\/span><\/p>

Other applications include<\/span> fake news detection<\/b>, development of robust algorithms for autonomous driving systems, improving counterfactual inference in observational studies, and making deep neural networks more robust for image classification.\u00a0<\/span><\/p>

In short, it can be applied anywhere that uses machine learning systems for decision-making.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

\n\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"Adversarial\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t

Why does it matters?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

Adversarial Machine Learning (AML) matters because it is crucial for <\/span>protecting ML algorithms<\/b>, which are widely used in contemporary technology applications. These systems can be manipulated by adversaries posing security threats, thus, maintaining their robustness against attacks is essential.\u00a0<\/span><\/p>

Moreover, the exploration of this approach can benefit various ML problems, leading to advancements in fields such as unsupervised learning, natural language processing, and reinforcement learning.\u00a0<\/span><\/p>

The framework also has direct applications in defending against fake news, developing robust algorithms, improving observational studies, and enhancing adversarial robustness.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t

Adversarial Machine Learning: Bayesian Perspectives<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

Journal of the American Statistical Association<\/span>, 2023<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\"\"<\/a>\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tVictor Gallego <\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tChief Research Officer<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tGame Theory, Cybersecurity<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t<\/path><\/svg>\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\tSource<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"Adversarial\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t
<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t

Other publications<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t\t
\n\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"renewable\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"Pomeron\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"Poor\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t

Machine Learning Nowcasting Of PV Energy Using Satellite Data<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t

Pomeron Physics at the LHC<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t

Poor self\u2010reported sleep is associated with risk factors for cardiovascular disease<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

Machine learning models to improve photovoltaic (PV) energy production prediction in Spain benefiting sectors like renewable energy and finance.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

The study uses Regge Theory and Pomeron exchange to enhance understanding of hadron collisions. In the long term, it influences advancements in areas like quantum computing, medical technology, defense, and energy.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

The study indicates a link between poor sleep and increased cardiovascular disease risk. Emphasizing the need for sleep improvements in health strategies and policies.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tRenewable energy, Predictive Analytics<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tParticle Physics, Big Data<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tData Analytics, Public health<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

Learn More >><\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

Learn More >><\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

Learn More >><\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"

Adversarial Machine Learning: Bayesian Perspectives Journal of the American Statistical Association, 2023 Abstract Adversarial Machine Learning (AML) is a growing field focused on defending Machine Learning (ML) systems from security threats where adversaries manipulate input data to deceive these systems. While most AML work relies on game-theoretic modeling of the conflict between an ML system […]<\/p>","protected":false},"author":1,"featured_media":8730,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"yoast_head":"\nAdversarial Machine Learning: Bayesian Perspectives - Komorebi AI<\/title>\n<meta name=\"description\" content=\"Bayesian approach boosts defense against security threats in Machine Learning systems, relevant to cybersecurity and language processing.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/komorebi.ai\/en\/adversarial-machine-learning-bayesian-perspectives\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Adversarial Machine Learning: Bayesian Perspectives - Komorebi AI\" \/>\n<meta property=\"og:description\" content=\"Bayesian approach boosts defense against security threats in Machine Learning systems, relevant to cybersecurity and language processing.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/komorebi.ai\/en\/adversarial-machine-learning-bayesian-perspectives\/\" \/>\n<meta property=\"og:site_name\" content=\"Komorebi AI\" \/>\n<meta property=\"article:modified_time\" content=\"2023-09-21T14:15:13+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/komorebi.ai\/wp-content\/uploads\/2023\/07\/ciberseguridad-2.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"2000\" \/>\n\t<meta property=\"og:image:height\" content=\"1334\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"4 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/komorebi.ai\/adversarial-machine-learning-bayesian-perspectives\/\",\"url\":\"https:\/\/komorebi.ai\/adversarial-machine-learning-bayesian-perspectives\/\",\"name\":\"Adversarial Machine Learning: Bayesian Perspectives - Komorebi AI\",\"isPartOf\":{\"@id\":\"https:\/\/komorebi.ai\/es\/#website\"},\"datePublished\":\"2023-07-21T10:53:53+00:00\",\"dateModified\":\"2023-09-21T14:15:13+00:00\",\"description\":\"Bayesian approach boosts defense against security threats in Machine Learning systems, relevant to cybersecurity and language processing.\",\"breadcrumb\":{\"@id\":\"https:\/\/komorebi.ai\/adversarial-machine-learning-bayesian-perspectives\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/komorebi.ai\/adversarial-machine-learning-bayesian-perspectives\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/komorebi.ai\/adversarial-machine-learning-bayesian-perspectives\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Portada\",\"item\":\"https:\/\/komorebi.ai\/es\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Adversarial Machine Learning: Bayesian Perspectives\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/komorebi.ai\/es\/#website\",\"url\":\"https:\/\/komorebi.ai\/es\/\",\"name\":\"Komorebi AI\",\"description\":\"Komorebi\",\"publisher\":{\"@id\":\"https:\/\/komorebi.ai\/es\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/komorebi.ai\/es\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"en-US\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/komorebi.ai\/es\/#organization\",\"name\":\"Komorebi AI\",\"url\":\"https:\/\/komorebi.ai\/es\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/komorebi.ai\/es\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/komorebi.ai\/wp-content\/uploads\/2022\/07\/isologotipo_normal.png\",\"contentUrl\":\"https:\/\/komorebi.ai\/wp-content\/uploads\/2022\/07\/isologotipo_normal.png\",\"width\":456,\"height\":277,\"caption\":\"Komorebi AI\"},\"image\":{\"@id\":\"https:\/\/komorebi.ai\/es\/#\/schema\/logo\/image\/\"}}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Adversarial Machine Learning: Bayesian Perspectives - Komorebi AI","description":"Bayesian approach boosts defense against security threats in Machine Learning systems, relevant to cybersecurity and language processing.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/komorebi.ai\/en\/adversarial-machine-learning-bayesian-perspectives\/","og_locale":"en_US","og_type":"article","og_title":"Adversarial Machine Learning: Bayesian Perspectives - Komorebi AI","og_description":"Bayesian approach boosts defense against security threats in Machine Learning systems, relevant to cybersecurity and language processing.","og_url":"https:\/\/komorebi.ai\/en\/adversarial-machine-learning-bayesian-perspectives\/","og_site_name":"Komorebi AI","article_modified_time":"2023-09-21T14:15:13+00:00","og_image":[{"width":2000,"height":1334,"url":"https:\/\/komorebi.ai\/wp-content\/uploads\/2023\/07\/ciberseguridad-2.jpg","type":"image\/jpeg"}],"twitter_card":"summary_large_image","twitter_misc":{"Est. reading time":"4 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/komorebi.ai\/adversarial-machine-learning-bayesian-perspectives\/","url":"https:\/\/komorebi.ai\/adversarial-machine-learning-bayesian-perspectives\/","name":"Adversarial Machine Learning: Bayesian Perspectives - Komorebi AI","isPartOf":{"@id":"https:\/\/komorebi.ai\/es\/#website"},"datePublished":"2023-07-21T10:53:53+00:00","dateModified":"2023-09-21T14:15:13+00:00","description":"Bayesian approach boosts defense against security threats in Machine Learning systems, relevant to cybersecurity and language processing.","breadcrumb":{"@id":"https:\/\/komorebi.ai\/adversarial-machine-learning-bayesian-perspectives\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/komorebi.ai\/adversarial-machine-learning-bayesian-perspectives\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/komorebi.ai\/adversarial-machine-learning-bayesian-perspectives\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Portada","item":"https:\/\/komorebi.ai\/es\/"},{"@type":"ListItem","position":2,"name":"Adversarial Machine Learning: Bayesian Perspectives"}]},{"@type":"WebSite","@id":"https:\/\/komorebi.ai\/es\/#website","url":"https:\/\/komorebi.ai\/es\/","name":"Komorebi AI","description":"Komorebi","publisher":{"@id":"https:\/\/komorebi.ai\/es\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/komorebi.ai\/es\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/komorebi.ai\/es\/#organization","name":"Komorebi AI","url":"https:\/\/komorebi.ai\/es\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/komorebi.ai\/es\/#\/schema\/logo\/image\/","url":"https:\/\/komorebi.ai\/wp-content\/uploads\/2022\/07\/isologotipo_normal.png","contentUrl":"https:\/\/komorebi.ai\/wp-content\/uploads\/2022\/07\/isologotipo_normal.png","width":456,"height":277,"caption":"Komorebi AI"},"image":{"@id":"https:\/\/komorebi.ai\/es\/#\/schema\/logo\/image\/"}}]}},"_links":{"self":[{"href":"https:\/\/komorebi.ai\/en\/wp-json\/wp\/v2\/pages\/8622"}],"collection":[{"href":"https:\/\/komorebi.ai\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/komorebi.ai\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/komorebi.ai\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/komorebi.ai\/en\/wp-json\/wp\/v2\/comments?post=8622"}],"version-history":[{"count":47,"href":"https:\/\/komorebi.ai\/en\/wp-json\/wp\/v2\/pages\/8622\/revisions"}],"predecessor-version":[{"id":9852,"href":"https:\/\/komorebi.ai\/en\/wp-json\/wp\/v2\/pages\/8622\/revisions\/9852"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/komorebi.ai\/en\/wp-json\/wp\/v2\/media\/8730"}],"wp:attachment":[{"href":"https:\/\/komorebi.ai\/en\/wp-json\/wp\/v2\/media?parent=8622"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}