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Machine Learning Models in Industrial Blockchain, Attacks and Contribution

  • The importance of machine learning has been increasing dramatically for years. From assistance systems to production optimisation to support the health sector, almost every area of daily life and industry comes into contact with machine learning. Besides all the benefits that ML brings, the lack of transparency and the difficulty in creating traceability pose major risks. While there are solutionsThe importance of machine learning has been increasing dramatically for years. From assistance systems to production optimisation to support the health sector, almost every area of daily life and industry comes into contact with machine learning. Besides all the benefits that ML brings, the lack of transparency and the difficulty in creating traceability pose major risks. While there are solutions that make the training of machine learning models more transparent, traceability is still a major challenge. Ensuring the identity of a model is another challenge. Unnoticed modification of a model is also a danger when using ML. One solution is to create an ML birth certificate and an ML family tree secured by blockchain technology. Important information about training and changes to the model through retraining can be stored in a blockchain and accessed by any user to create more security and traceability about an ML model.show moreshow less

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Metadaten
Document Type:Conference Proceeding
Title (English):Machine Learning Models in Industrial Blockchain, Attacks and Contribution
Author:Fatemeh Ghovanlooy GhajarORCiDGND, Axel SikoraORCiDGND, Jan Stodt, Christoph Reich
Year of Publication:2022
First Page:106
Last Page:111
Parent Title (English):The Upper-Rhine Artificial Intelligence Symposium (UR-AI 2022) : AI Applications in Medicine and Manufacturing
Editor:Christoph Reich, Ulrich Mescheder
ISBN:978-3-00-073638-4 (e-ISBN)
ISBN:978-3-00-073637-7 (Print)
URL:https://www.researchgate.net/publication/364343172
Language:English
Institutes:Forschung / ivESK - Institut für verlässliche Embedded Systems und Kommunikationselektronik
Fakultät Elektrotechnik, Medizintechnik und Informatik (EMI) (ab 04/2019)
Institutes:Bibliografie
Tag:Blockchain; Machine learning; Security; Traceability
Open Access: Open Access 
 Diamond 
Relevance:Konferenzbeitrag: h5-Index < 30
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International
Comment:
Konferenz: The Upper-Rhine Artificial Intelligence Symposium (4th UR-AI Symposium), Villingen-Schwenningen, 19 October 2022