Cargando…
Experiments on Adversarial Examples for Deep Learning Model Using Multimodal Sensors
Recently, artificial intelligence (AI) based on IoT sensors has been widely used, which has increased the risk of attacks targeting AI. Adversarial examples are among the most serious types of attacks in which the attacker designs inputs that can cause the machine learning system to generate incorre...
Autores principales: | Kurniawan, Ade, Ohsita, Yuichi, Murata, Masayuki |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9696998/ https://www.ncbi.nlm.nih.gov/pubmed/36433250 http://dx.doi.org/10.3390/s22228642 |
Ejemplares similares
-
Minimum Adversarial Examples
por: Du, Zhenyu, et al.
Publicado: (2022) -
Experimental demonstration of adversarial examples in learning topological phases
por: Zhang, Huili, et al.
Publicado: (2022) -
Adversarial Examples—Security Threats to COVID-19 Deep Learning Systems in Medical IoT Devices
Publicado: (2020) -
Analysis of the Correlation between Frontal Alpha Asymmetry of Electroencephalography and Short-Term Subjective Well-Being Changes
por: Wutzl, Betty, et al.
Publicado: (2023) -
Adversarial Machine Learning Protection Using the Example of Evasion Attacks on Medical Images
por: Rudnitskaya, E. A., et al.
Publicado: (2023)