%CE%91%CE%BD%CF%84%CE%B9%CF%80%CE%B1%CF%81%CE%B1%CE%B8%CE%B5%CF%84%CE%B9%CE%BA%CE%AE_%CE%BC%CE%B7%CF%87%CE%B1%CE%BD%CE%B9%CE%BA%CE%AE_%CE%BC%CE%AC%CE%B8%CE%B7%CF%83%CE%B7Adversarial_machine_learning%DB%8C%D8%A7%D8%AF%DA%AF%DB%8C%D8%B1%DB%8C_%D9%85%D8%A7%D8%B4%DB%8C%D9%86_%D8%AE%D8%B5%D9%85%D8%A7%D9%86%D9%87Q20312394
about
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection MethodsA Simple Method to Determine if a Music Information Retrieval System is a “Horse”Houdini: Fooling Deep Structured Visual and Speech Recognition Models with Adversarial ExamplesIntriguing properties of neural networksAudio Adversarial Examples: Targeted Attacks on Speech-to-TextObfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial ExamplesDistillation as a Defense to Adversarial Perturbations against Deep Neural NetworksOne pixel attack for fooling deep neural networksPixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial ExamplesAdversarial PatchInvisible Mask: Practical Attacks on Face Recognition with InfraredDeep Learning and Music AdversariesText Analysis for Decision Making under Adversarial EnvironmentsSemi-adversarial Networks: Convolutional Autoencoders for Imparting Privacy to Face ImagesMaking machine learning robust against adversarial inputsExcessive Invariance Causes Adversarial Vulnerability
P921
Q30085931-b253f257-4a5e-9694-6a76-8fa7f3c7da62Q30331500-6dede874-47f1-c46f-5c88-cd15445709e6Q44653859-07040cce-4e96-9793-a150-bac27ce55dfcQ45318764-509400e4-458e-84aa-3de4-287d32219da1Q47342792-d91e290c-4bf0-034d-a5af-a8c454d34234Q48534215-5fcc82d7-49a2-0a50-b301-7b760c90e198Q48534434-e0ffc74e-4ed4-884f-3187-bd03135ad97fQ50068235-4624d96a-4f13-29f4-d113-5486361ce1aaQ50188193-b80b5061-4fc8-2d07-a919-17c40957f888Q51128578-7aa48321-4aa6-d8dc-926c-250b3d3bcb51Q51130749-e722d643-44df-a75f-67e6-64aac0e43fffQ54245290-ab1f277d-4fc1-3c94-0d48-3370f8c87bb6Q55475201-64d16162-46a5-2714-e5ab-4e2e2a53d363Q56875639-fcc8764f-445f-aa65-28f0-846421dcfad3Q61822439-53b39c2e-4d9e-b2f2-add0-4f76c569dc75Q62428109-86a9b527-4f71-6c5c-d016-392025de40d9
P921
description
research field that lies at the intersection of machine learning and computer security
@en
name
adversarial machine learning
@en
aprendizaje automático adversativo
@es
Αντιπαραθετική μηχανική μάθηση
@el
Суперницьке машинне навчання
@uk
یادگیری ماشین خصمانه
@fa
对抗机器学习
@zh
type
label
adversarial machine learning
@en
aprendizaje automático adversativo
@es
Αντιπαραθετική μηχανική μάθηση
@el
Суперницьке машинне навчання
@uk
یادگیری ماشین خصمانه
@fa
对抗机器学习
@zh
prefLabel
adversarial machine learning
@en
aprendizaje automático adversativo
@es
Αντιπαραθετική μηχανική μάθηση
@el
Суперницьке машинне навчання
@uk
یادگیری ماشین خصمانه
@fa
对抗机器学习
@zh
P6366
P2179
P279
P6366
2778403875