A Supply Chain Management System to Prevent Counterfeiting and

Trace Different Transactions Instead of using PUF Device

Yusuke Abe

, Kosei Arisaka

, Kitahiro Kaneda

and Keiichi Iwamura

Tokyo University of Science, 6-3-1 Nijuku, Katsushika-ku, Tokyo 125-8585, Japan

NAGASE & CO., LTD., 5-1 Nihonbashi-Kobunacho, Chuo-ku, Tokyo 103-8355, Japan

Keywords: 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 distinguish 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.

1 INTRODUCTION

Logistics has evolved over the years with the

dramatic advances in information technology (IT),

and has become an inseparable part of modern life.

Here, the distribution process from the procurement

of raw material to the delivery of products to

consumers is called the supply chain. The supply

chain consists of suppliers, logistics providers,

wholesalers, retailers, and end users. To improve the

added value of products and services for customers, a

management system that optimizes the integrated

management of objects, money, and information has

been attracting attention in recent years. This is

known as supply chain management (SCM).

Companies involved in the supply chain are aware

of SCM and focus on how to provide products

efficiently. Therefore, damage caused by counterfeits

around the world still cannot be stopped. A report

(OECD and EUIPO, 2016, 2019) by the Organisation

for Economic Cooperation and Development

(OECD) and the European Union’s (EU) Intellectual

Property Office explains that the global trade value of

counterfeit and pirated goods reached $461 billion in

2013 and $509 billion in 2016. For example, have you

ever wondered whether the product you purchased

through e-commerce is authentic and has been

delivered to you through the right channels? To

eliminate such concerns, products are currently

managed through the physical attachment of radio-

frequency identification (RFID) tags or barcodes (QR

codes). For those with malicious intent, however, it is

easy to physically remove such tags or codes from the

products. This makes it possible to attach the original

RFID or barcode to a fake product and sell the

counterfeit. When such an attack occurs, it is usually

very difficult for end users to determine the

authenticity of the product, necessitating counter-

measures. In addition, each company manages its own

transaction history. Even if the end user reads the

information from the tag, the user will only be able to

view the information that has been made accessible to

the public at the discretion of the individual company.

Given this background, technologies such as

blockchain and PUF are expected to be used. As for

the information the user browses, it is expected that

blockchain, which is a distributed ledger that is

difficult to tamper with, will be introduced into SCM.

This technology can be used to track products with

reliability. For intentional tag replacement, an

individual identification system that uses a

technology called physical unclonable function

Abe, Y., Arisaka, K., Kaneda, K. and Iwamura, K.

A Supply Chain Management System to Prevent Counterfeiting and Trace Different Transactions Instead of using PUF Device.

DOI: 10.5220/0010571301010108

In Proceedings of the 18th International Conference on e-Business (ICE-B 2021), pages 101-108

ISBN: 978-989-758-527-2

101

(PUF) has been proposed, instead of information that

is externally attached to products, such as RFID or

barcodes. PUF is a function that outputs different

eigenvalues for each object, utilizing unique physical

properties of the product that are difficult to replicate.

For example, when a semiconductor chip with the

same circuit receives the same input, the output is the

same for all chips, but the response time is slightly

different. This technology identifies individual chips

with the same circuit using the difference in response

time as a unique property of the device, which makes

it difficult to duplicate. A buyer of the device can

determine the authenticity by utilizing this feature.

However, PUF has a drawback in that it cannot be

applied to all products. Due to PUF’s features, it is

limited to a very small number of products, such as

semiconductor chips. The technology is not versatile

and cannot cover a wide variety of commerce. In this

paper, we propose a system that can perform the same

functions as PUF for a range of materials (powders,

liquids, individuals, precious metals, etc.) as

examples of a commodity supply chain for which

PUF cannot be used. Mere substances are often

identified by their composition and size, and few

individual identification technologies, like PUF, have

been studied that clearly confirm the match. It is,

however, possible to judge if a product is legitimate

based on whether it meets a criterion. This judgment

is called normal judgment. In normal judgment, by

measuring the physical properties of a product, a

substance that has the specified components and size

is judged to be genuine, and a substance that does not

meet the specified components and size is judged to

be fake. Accordingly, when an end user purchases

and receives a substance, it is preferable to have a

technology that not only determines whether the

product is legitimate by satisfying the specified

features, but also utilizes unpredictable values like

PUF. Hence, the main goal is to realize an SCM

system that can be used for various products, with or

without the application of PUF.

The remainder of this paper is organized as

follows. Chapter 2 explains the related work against

counterfeits, Chapter 3 describes the proposed

methods, Chapter 4 is devoted to the evaluation, and

Chapter 5 provides a summary.

2 RELATED WORK

2.1 Blockchain in Supply Chain

Current supply chains have difficulty in tracking

product history (traceability). Even if consumers view

the product history, they cannot determine if the data

such as “who”, “when”, “where”, “what”, and “how”

are correct. Therefore, a platform for sharing accurate

information is needed, and there is a lot of research

being done on the use of blockchain, a secure and

highly available distributed ledger. Dietrich et al.

(2021) and Pournader et al. (2020) survey and review

many blockchain projects in the supply chain.

Hackius et al. (2017) sought input from logistics

experts and found that most experts are positive. Tijan

et al. (2019) argue that blockchain can minimize

major issues in logistics such as order delays, errors,

and multiple data entry.

2.2 Detection of Counterfeiting

This section lists the issues regarding RFID-based

external tag technology, PUF-based technology, and

identification by substance features. The study of the

issues is a stepping stone in proposing effective

methods.

Sun et al. (2019) claim that RFID and the

information associated with it cannot be tampered

with, and that different users are provided with

different query permissions to maintain their

authenticity. Toyoda et al. (2017) argue that end users

can reject counterfeits by having each entity transfer

products and their ownership while determining the

authenticity of the RFID tags. No matter how much

the authenticity of the tag is guaranteed, as shown by

Sun et al. (2019) and Toyoda et al. (2017), an end user

has no way of checking the authenticity of the content.

The physical space where products exist and the

cyberspace where authenticity is guaranteed are not

well connected. The use of RFID tag anti-

counterfeiting technology with PUF, as described by

Devadas et al. (2008), is therefore not a sufficient

solution.

Previous studies (Hori et al., 2015; Aniello et al.,

2019; Negka et al., 2019) focus mainly on individual

identification systems that utilize PUF.

Three points are worth noting. First, as mentioned

previously, PUF can only be applied to specific

products. Target products need to be expanded to

meet a wide range of modern needs. Second, noise

reduction technology, called a fuzzy extractor (Dodis

et al., 2004), is required. When using PUF, ideally, a

certain semiconductor chip should always produce a

same output, but in reality, it is difficult because of its

vulnerability to noise. In addition, PUF uses a minute

variation in each semiconductor chip. There are

therefore problems such as not being able to get an

appropriate output or getting a similar output from

different devices. Fuzzy extractor is a means to solve

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this problem. However, installing a fuzzy extractor

makes the process more complicated and increases

the processing time and circuit size. This is also a

factor that increases implementation costs. Third,

systems that use PUF only determine whether the

device shipped and the device delivered to the end

user is an exact match. Strictly speaking, this is not an

authenticity judgment. This just verifies that the end

user has received the product declared by the supplier.

However, it is generally not important for the end user

that the shipment and purchased product are identical.

In many cases, it is important that the product meets

a required criterion and is legitimate. Consider, for

example, the situation in which a diamond is

purchased from a catalog. The purchaser does not

necessarily want a diamond that is exactly the same

as the picture in the catalog. It is important that the

diamond’s carats, hardness, and size meet the criteria.

The system proposed by Koike (2010) verifies

legitimacy based on the features extracted from the

target object. The normal judgment is more

predictable than PUF because the judgment value of

a legitimate device is fixed. We take the example of a

diamond once again. An attacker realizes that if a

product has a specified range of carat, hardness, and

size, it is considered real. In this case, even if the

identification target is out of range, the attacker can

pass off a counterfeit as genuine by creating a device

that outputs a judgment value satisfying the criteria.

By the way, it is difficult to predict an output of PUF,

even if the value of one device is stored, it cannot be

diverted to other devices. The normal judgment does

not have this feature of PUF. Therefore, there are few

proposals for judgment systems based on features of

objects.

In summary, technology is required to output

different values for each individual (or each

transaction between companies), similar to PUF,

without fixing the output value of the normal

judgment. This prevents fraud by logistics providers.

3 PROPOSED METHOD

3.1 Overview

In this study, we propose a technology to determine

authenticity by normal judgment. The goal of the

proposed system is to achieve the same functionality

as PUF for the SCM of substances that have been

difficult to identify in the past. The system consists of

a registration device, verification device, and

identification device, as shown in Figure 1. The

registration device in SCM is assumed to be used by

suppliers who generate and ship products. A

verification device is used by logistics providers who

transport products. The identification device is used

by end users who receive the products. The focus is

on commercial transactions; therefore, suppliers and

end users have no incentive to commit fraud, and

fraud or errors by outsiders or logistics providers can

be controlled. Furthermore, each function is realized

by blockchain, which improves the common

information management and traceability among

other companies. Blockchain improves the efficiency

of the entire SCM and clarifies where responsibility

lies. The following sections describe in detail the

algorithms of the registration device in Section 3.2,

the verification device in Section 3.3, and the

identification device in Section 3.4.

3.2 Registration Device

The registration device is handled by a supplier. It

serves to generate a product-specific key and registers

the key in the blockchain by inputting the feature

values of the product and information, which are

different for each product. This device consists of

four elements: measurement, judgment, generation,

and registration.

The measurement section extracts the feature

value from the target as input signal P1 and outputs

the measurement value.

The judgment section determines whether the

product is legitimate based on the value obtained

from the measurement section. For this purpose, the

feature value to be acquired for each product and its

legitimate range are set in advance. A judgment value

is output after determining that the product is

legitimate if within the range, and that it is

illegitimate if it is outside the range. The value is then

expressed as a relatively large bit string of 128 bits,

for example, as binary values of legitimate or not

legitimate. In this way, noise reduction technology is

no longer necessary and the judgment result is

effective in suppressing forgery.

The generation section concatenates the judgment

value and “transaction information” U1 unique to

each product, which is independent of the product

features. Concatenation is performed by an exclusive

disjunction. A hash of the concatenated values is then

generated as the identification key, Key1. Transaction

information identifies products and utilizes, for

example, the manufacturer, serial number,

temperature, number of verifications, and random

numbers. There are no obstacles even if outsiders

possess the same type of product. This is because the

judgment value is not output to the outside of the

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103

Figure 1: Overview of the system.

device and is kept secret by transaction information,

including random numbers. Therefore, the

identification key becomes random and unpredictable

for each transaction.

The registration section links the information to

be verified with the information to identify it. First,

“verification information” is generated by hashing to

use the Key1 output from the generation section.

Then, “identification information” is utilized to

identify the information corresponding to the product

for which judgment is conducted from among a large

amount of verification information. The identification

information applies to the manufacturer and serial

number pair that is part of the transaction information.

Finally, the generated verification and identification

information are mapped and registered in the

blockchain. Owing to the features of the blockchain,

all values are made public. If Key1 is made public as

is and a malicious logistics provider forges a

verification device to output the value, an end user

may be fooled. To prevent fraud, Key1 is hashed and

the identification key is unpredictable.

The following shows the specific flow of the

registration device.

(1) A supplier inputs an input signal P1, which

depends on the product’s features and transaction

information U1.

(2) The judgment section determines whether the

measurement results are valid.

(3) The generation section generates Key1 from the

judgment value and transaction information.

(4) The registration section generates verification

information from Key1 and registers it in the

blockchain with identification information.

3.3 Verification Device

The verification device is a device handled by the

deliverer who transports the product. In much the

same way as the registration device, a product-

specific key is generated by inputting product features

and transaction information, which are different for

each product. At this point, the end user, who is

notified by the supplier, can input the transaction

information and make a judgment using the product

to confirm its legitimacy. This device consists of four

elements: measurement, judgment, generation, and

output.

The measurement section measures a feature

value of the target as an input signal P2 and outputs a

measurement value.

The judgment section outputs a judgment value

based on the acquired measurement values. It

determines that the product is legitimate if it is within

the pre-set range and illegitimate if it is outside the

range.

The generation section concatenates the judgment

value and “transaction information” U2 unique to

each product, which is independent of the product’s

features. Concatenation is performed by an exclusive

disjunction. A hash of the concatenated values is then

generated as the identification key, Key2. When an

end user purchases a product, the information used in

the registration device is notified by the supplier as

transaction information.

The output section provides Key2 generated by

the generation section to the identification device.

In the proposed method, the verification device

consists of four parts: measurement, judgment,

generation, and output. It can be implemented freely

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according to the application, such as by installing a

generation and output section in the identification

device described below. The measurement, judgment,

and generation sections are the same as those in the

registration device. Thus, if an input signal P2 and

transaction information U2 input to the verification

device are identical to the input signal P1 and the

transaction information U1 input to the registration

device, it is obvious that Key2 without noise is always

equal to Key1. There is also no property that the key

is slightly different each time as in SCM using PUF.

Since there is no need to implement techniques such

as a fuzzy extractor, it is not necessary to consider the

increase in processing time and implementation cost.

The specific flow of the verification device is as

follows.

(1) A user provides input signal P2 and transaction

information U2 to the device.

(2) The judgment section determines whether the

measurement results are valid.

(3) The generation section generates Key2 from the

judgment value and transaction information.

(4) The output section outputs Key2 to the

identification device.

3.4 Identification Device

The identification device is a device that is handled

by an end user. It checks whether the verification

information (hash of Key1) registered in the

blockchain matches the value of hashed Key2 from

the verification device presented by the deliverer.

This process confirms the authenticity of the product.

This device consists of three elements: acquisition,

verification, and registration.

The acquisition section obtains verification

information from the blockchain based on the

identification information, and obtains Key2 from the

verification device. The identification information is

extracted using part of the transaction information

provided by the supplier to the end user in this process.

The verification section checks for consistency

between the verification information and the

information in Key2. Specifically, Key2 is hashed,

and whether the hash matches the verification

information is examined. If it matches, the section

outputs the success information to the registration

section, indicating that the verification is successful.

The registration section links the “verified

information” to the verification information when it

is successfully verified and registers it in the

blockchain. The information with the verified

information is restricted so that it cannot be verified

again when verified later. This prevents the same

transaction information from being used in a

malicious manner.

The specific flow of the identification device is as

follows.

(1) The acquisition section obtains Key2 from the

verification device. Additionally, it searches the

blockchain based on the input identification

information, and obtains verification information

if the verified information is not attached.

(2) The verification section hashes Key2 obtained in

(1). It verifies whether the hash value matches the

verification information and outputs the result.

(3) The registration section adds the verified

information to the identification information if the

result is valid. This is then registered in the

blockchain.

4 EVALUATION

To evaluate the proposed method, we discuss possible

attacks in Section 4.1. Section 4.2 presents a

comparison with conventional SCM using barcodes,

RFID, mere substances, and PUF. Furthermore, the

implementation cost is described in Section 4.3.

4.1 Attacks on the Proposed Method

4.1.1 Fraud by Logistics Providers

The simplest example of a supply chain is a supplier,

a logistics provider, and an end user. It is assumed that

there is no fraud in the commercial transactions

between a supplier and an end user because they can

simply terminate the contract if they are dissatisfied

with the other party. The main possible source of an

attack is that the logistics provider may swap the

authentic item with a counterfeit and the end user

receives a counterfeit. In general, an end user does not

have a large-scale verification device. The

verification is carried out using a verification device

owned by a logistics provider for authenticity

judgment or normal judgment. The following is an

example of a diamond transaction. If a diamond is

simply swapped with an object that is not a diamond,

such as zircon or zirconia, it can be easily detected as

unjustified. However, even if the object is a fake that

does not fit into the range, it is possible to make the

fake real by forging the device.

The proposed method counters this attack by

generating a different key for each transaction. The

term “transaction” in this context does not refer to the

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entire commercial transaction between a supplier and

an end user. Instead, it refers to transactions between

companies, such as transactions between a supplier

and a logistics provider, and transactions between a

logistics provider and an end user. The following

describes the countermeasure method in detail.

The success or failure of the normal judgment for

input signal P2 is noted, but the judgment value itself

is not output. It is also difficult to obtain the value

from the outside by analyzing the device. The

judgment value is then secreted into the device using

transaction information U2, including random

numbers, and output as the identification key Key2.

The random number is known only to the supplier and

the end user. Key2 is difficult to predict unless the

judgment value is leaked to the outside and

randomness is maintained as long as the random

number is not known. In summary, the judgment

value is not output to the outside of the device but is

kept secret in the transaction information to generate

Key2, which is difficult to predict and random. This

means that even if PUF is not applicable to the target,

the function is equivalent to that of PUF. Furthermore,

a logistics provider does not have the advantage of

storing the Key2 value; because they generate a

unique identification key for each transaction, it is

meaningless and cannot be used for other transactions.

This feature is not found in PUF. In addition, by

adding verified information to the transaction once it

is used, the system prevents unauthorized double use.

Unless a famous brand adds verified information to

its own products, it will be possible for an unknown

brand to sell its products fraudulently. Using the

identification information in the blockchain, an

unknown brand can falsely sell products that are

identical to the quality of a famous brand. The

products are indistinguishable from those of famous

brands. It is therefore necessary to add the verified

information to the verification information used to

limit double use. However, even if the information is

verified once, it can be verified again. The number of

verifications included in the transaction information

is added by one, and the verification information for

that is generated. By registering this information, a

new verification can be performed.

4.1.2 Blockchain-based Attacks

A blockchain is a public ledger. Therefore, a third party

can view the blockchain to obtain information about

transactions. This subsection describes the study of the

possibility of fraud using the proposed method.

The only information to be registered in the

blockchain is identification and verification

information. The identification information is used to

obtain verification information for the corresponding

transaction from the blockchain. It is created using

part of the transaction information. In the proposed

method, when a product is registered, a supplier

notifies all transaction information only to the end

user through a secure channel. The system works

properly only when the product meets the required

standard, and the correct transaction information is

entered. Even if an outsider obtains the identification

and verification information by browsing the

blockchain, he/she will not be able to know the

transaction information, such as random numbers. It

is not possible to generate the correct Key2. Thus,

there is no room for an outsider to show the

authenticity of the product using the proposed

method. In addition, it is very difficult to falsify the

identification and verification information published

on blockchain, and attacks using such information are

hard. This is because blockchains are virtually

impossible to tamper with in terms of computational

complexity.

4.2 Comparison with Conventional

Methods

The proposed method and conventional methods are

compared from four perspectives, as shown in Table 1.

Conventional methods include SCM with external

tags using barcodes or RFID, SCM utilizing mere

substances, and SCM using PUF.

The method using PUF is superior in that it

provides an exact match between the shipment and

the product received. This is not necessarily

important, however. The fact that the product is

verified as legitimate is generally sufficient.

Furthermore, fraud is possible if a verification

device's output indication for a shipped PUF device is

forged. Using external tags or mere substances is also

flawed in both respects and cannot dispel concerns of

end users. It is difficult to determine whether a

product is legitimate if an attacker removes a barcode

or RFID tag and attaches it to a counterfeit product,

or replaces only contents. In the case of mere

substances, an end user cannot know an exact result

as long as an attacker can produce a verification

device to tamper with an output. On the other hand,

the proposed method does not fix a judgment value

but outputs it randomly for each transaction, so it is

possible to determine whether a product is legitimate.

This method does not use PUF. However, it provides

advantages of unpredictability and randomness like

PUF. It can also be applied to products that can use

PUF.

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Table 1: Comparison with conventional methods (1=lowest; 3=highest).

Method

Exact match with

the shipment

Legitimate product Cost

Distinction per

transaction

Proposed method 2 3 1 3

External tag

(Barcode/RFID)

1 1 3 1

Mere material 2 2 1 1

PUF 3 2 1 1

External tags are the best in terms of cost, and

although they are not as secure, they are relatively

easy to install in existing systems. The other three

methods are not so simple, as they consist of

somewhat complex systems to detect counterfeit

products. However, there is a trade-off between high

security and cost (simplicity), and supply chain

members must pursue what users want.

The distinguishing feature between each

transaction is found only in the proposed method. For

example, the PUF-based method does not distinguish

between each transaction in the process of product

flow from user A to user B to user C. The proposed

method can generate individualized unique keys

using transaction information in the process of

product flow from user A to user B and from user B

to user C. Double use such as unauthorized resale or

diversion can thus be prevented, and suppliers can

understand how the products they sell are resold. This

is important for ensuring traceability and safety for

users.

4.3 Simulation

A blockchain substrate called Ethereum was used to

simulate the proposed method from the viewpoint of

ease of development and payment in virtual currency.

Ethereum generates a fee every time a smart contract

is executed. This provides incentives to miners, who

are responsible for approving transactions and

keeping the blockchain secure. The fee is managed in

units called gas. The behaviors of the registration,

verification, and identification devices were checked

in a test environment. Remix (2021), a web browser

integrated development environment (IDE) for

developers of the dedicated language Solidity, was

employed. Cost calculations were performed using

the rate on February 15, 2021. Etherscan (2021)

showed that the average gas price was 178.715 Gwei.

CoinGecko (2021) showed that the dollar rate was

1804.98 USD/ETH. The implementation cost of each

device was calculated as shown in Table 2.

“Transaction cost” used in Remix (Table 2) is

expressed as the sum of the commonly used

transaction cost and execution cost. The cost was high

due to the steep rise in the gas price and Ethereum rate.

The former involves the limitations of the current

processing power of Ethereum, that is, scalability

issues. The latter involves a complex combination of

factors, but the increase in the number of users and

the scalability problem can be cited as factors.

However, this is not the essence of the proposed

method. This is because other programs have

calculated similarly high costs. Although not

optimistic, the Ethereum Foundation is already

pushing for migration and integration into

Ethereum 2.0. This is expected to solve the

continuous rise in gas prices and make it possible to

advance to faster technology with lower costs.

Therefore, it is important to improve the system to an

advanced level, in parallel, while paying attention to

cost.

Table 2: Cost of each device.

Device Transaction cost [gas] Cost [USD]

Registration

device

84673 27.31

Verification

device

35050 11.31

Identification

device

34675 11.19

5 CONCLUSIONS

We proposed a method for determining authenticity

using normal judgments for supply chain

management. It has the feature of being able to

perform the same function as PUF for devices and

materials for which PUF has not yet been established.

The use of blockchain improves traceability within

the entire SCM and increases the difficulty of data

tampering. The weakness of the public ledger was

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107

overcome using an algorithm based on hash functions.

We will continue to study more secure and efficient

requirements for practical use, with the goal of

reducing the cost of implementation.

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