Authors:
Yusuke Abe
1
;
Kosei Arisaka
1
;
Kitahiro Kaneda
2
and
Keiichi Iwamura
1
Affiliations:
1
Tokyo University of Science, 6-3-1 Nijuku, Katsushika-ku, Tokyo 125-8585, Japan
;
2
NAGASE & CO., LTD., 5-1 Nihonbashi-Kobunacho, Chuo-ku, Tokyo 103-8355, Japan
Keyword(s):
Blockchain, Supply Chain, Raw Material, Physical Unclonable Function (PUF), Counterfeiting.
Abstract:
The distribution of counterfeit products in supply chains has been increasing in recent years. Physical unclonable function (PUF), which takes advantage of the difficulty of duplication inherent in devices, is attracting attention as a way to overcome this problem. However, PUF can only be applied to a few objects, notably semiconductor chips, and is, therefore, unable to cover the wide variety of products in a supply chain. Moreover, it is necessary to use noise reduction technology, such as a fuzzy extractor, to remove noise from the output through PUF. There is a concern that costs may increase to implement such technology. Therefore, this paper proposes a system that can perform the same function as PUF on objects for which PUF has not yet been established, without using noise reduction technology. An arbitrary feature of an object is measured, and if the feature satisfies a certain criterion, the object can be safely delivered. In addition, the proposed method is able to disting
uish between individual transactions between one company and another. This prevents unauthorized resale and diversion by controlling even the location of the products once they are dispatched from the supplier.
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