Verifiable Machine Learning Models in Industrial IoT via Blockchain
- The importance of machine learning (ML) has been increasing dramatically for years. From assistance systems to production optimisation to healthcare support, almost every area of daily life and industry is coming into contact with machine learning. Besides all the benefits ML brings, the lack of transparency and difficulty in creating traceability pose major risks. While solutions exist to makeThe importance of machine learning (ML) has been increasing dramatically for years. From assistance systems to production optimisation to healthcare support, almost every area of daily life and industry is coming into contact with machine learning. Besides all the benefits ML brings, the lack of transparency and difficulty in creating traceability pose major risks. While solutions exist to make the training of machine learning models more transparent, traceability is still a major challenge. Ensuring the identity of a model is another challenge, as unnoticed modification of a model is also a danger when using ML. This paper proposes to create an ML Birth Certificate and 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.…
Document Type: | Conference Proceeding |
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Conference Type: | Konferenzartikel |
Zitierlink: | https://opus.hs-offenburg.de/8389 | Bibliografische Angaben |
Title (English): | Verifiable Machine Learning Models in Industrial IoT via Blockchain |
Conference: | International Advanced Computing Conference (12. : December 16-17, 2022 : Hyderabad, India) |
Author: | Jan Stodt, Fatemeh Ghovanlooy GhajarORCiDGND, Christoph Reich, Nathan Clarke |
Edition: | 1. |
Year of Publication: | 2023 |
Place of publication: | Cham |
Publisher: | Springer |
First Page: | 66 |
Last Page: | 84 |
Parent Title (English): | Advanced Computing : 12th International Conference, IACC 2022, Hyderabad, India, December 16–17, 2022, Revised Selected Papers, Part II |
Editor: | Deepak Garg, V. A. Narayana, P. N. Suganthan, Jaume Anguera, Vijaya Kumar Koppula, Suneet Kumar Gupta |
Volume: | CCIS 1782 |
ISBN: | 978-3-031-35643-8 (Softcover) |
ISBN: | 978-3-031-35644-5 (eBook) |
ISSN: | 1865-0929 |
ISSN: | 1865-0937 (E-ISSN) |
DOI: | https://doi.org/10.1007/978-3-031-35644-5_6 |
Language: | English | Inhaltliche Informationen |
Institutes: | Forschung / ivESK - Institut für verlässliche Embedded Systems und Kommunikationselektronik |
Institutes: | Bibliografie |
Tag: | Blockchain; Cybersecurity; Machine learning; Poisoning; Verifiability | Formale Angaben |
Relevance: | Konferenzbeitrag: h5-Index < 30 |
Open Access: | Closed |
Licence (German): | Urheberrechtlich geschützt |