Trust Model Concept for IoT Blockchain Applications as Part of the Digital Transformation of Metrology
2. Blockchain as a Technical Solution for the Digital Transformation of Metrology
- The move to an increasingly paperless world, including reduced use of paper money;
- Continued introduction of digitization in all areas;
- The redefinition of the SI being likely to lead to increased availability of intrinsic standards;
- The IoT leading to increased size and complexity in measuring systems, with a proliferation of sensors; and
- Artificial intelligence becoming an increasingly important feature in the software of measuring instruments.
3. Oracle Types and Relevance for IoT Applications
- Monitoring the blockchain network to check for incoming user or smart contract requests for measured data.
- Performing some type of computation, such as calculating a median or more complex parameters from multiple oracle submissions (e.g., extended Kalman filter, see Section 3.5), and calculating a critical value for threshold defined in the calibration procedure.
- Verifying (sign) and sending measured (or calculated) data to the blockchain for processing by the smart contract.
3.1. Origins of Data That Oracles Provide to Blockchain-Based Applications
- Web content;
- Sensor data.
3.2. Types of Oracles for Use in Blockchain-Based Applications Regarding the Input/Output
- Software oracles—oracles that provide online information to the blockchain, e.g., additional data about the calibration document and laboratory.
- Hardware oracles—oracles that provide information from physical devices, in our case from IoT device, to the blockchain. According to the previous point (Section 3.1), i.e., dominant sensor data, it is expected that hardware oracles have higher usage in IoT applications than software oracles.
- Inbound oracles—oracles that provide smart contracts with data from the external world, e.g., from accreditation institutions.
- Outbound oracles—oracles that send information to the outside world, e.g., to users interested in measurement traceability.
- Consensus-based oracles—data passed to the blockchain are treated as a result of a consensus of multiple oracles, e.g., if it is required to decide about data based on multiple hardware oracles (sensors).
3.3. Number of Sources That Are Used by Oracles
- One sensor -> single-source oracle;
- Multiple sensors -> multiple-source oracle.
3.4. Validation of the Data That Oracles Provide to Blockchain-Based Applications
3.5. Security of Data Sent by Oracles
- Provide integrity, authenticity, and non-repudiation of legally relevant (LR) information ;
- Store and attest public keys from IoT devices and all other participants;
- Avoid a trusted-third-party cost with digital certificates;
- Provide a solution that does not depend on a trusted third party.
- Tampering oracle software—software tampering could be mitigated by creating a hash based on software code, i.e., any unauthorized change of code would be detected by unmatched hashes. However, there is also a possibility for an authorized change of code, e.g., through updates carried out online. To allow it, it is needed to have a public key infrastructure (PKI), so that each oracle (and its code) can be accessed online if the user has a corresponding key [14,15]. Thereby, it is needed to follow relevant standards as well. For instance, WELMEC  distinguishes legally relevant (LR) and legally non-relevant software (LNR). Of course, LR is the main target to be protected from unauthorized changes, but the protection of LNR could also raise the trust in measurement results.
- Tampering oracle hardware—anti-tampering techniques are generally divided into four categories: tamper prevention, tamper detection, tamper response and tamper evidence. They include various methods and safety mechanisms such as encapsulation and coating of the hardware device , anti-tamper switches, sensors and circuitry , unique hardware properties of the device , secure cryptographic processors and device boot procedure that is designed specifically to detect tampering that has occurred while the oracle has been without power supply .
- Tampering sensor input—the most challenging issue is detecting the tampering of sensor input. For instance, if we want to know the temperature of a warehouse, truck trailer in transport, etc., the question is how we can be sure that the sensor is not maliciously placed in a temperature-controlled location that is isolated from the location intended for measurements. The solution could be based on consensus-based oracles (see Section 3.2). However, using multiple sensors of the same type (e.g., classical temperature sensors) is not a practical solution because they can be simply manipulated in the same way as single sensors. A better approach would be combining different sensor types, which would complicate possible malicious manipulation, for instance, classical temperature sensors combined with computer vision to detect a change in sensor surroundings and with infrared cameras as additional sources for temperature data on surrounding surfaces. The final estimation of the measured value could be completed using extended Kalman filters or some other method to combine data from different sensors [35,36]. In this way, the in situ inspections of measuring instruments and field surveillance  could be replaced by remote checks via blockchain smart contracts. Of course, this kind of system would be fairly complicated, and it is important to analyze for which possible applications it could be cost-effective.
4. Trust Model Concept for IoT Blockchain
4.1. Applying the Blockchain Technology to the IoT Device Level
4.2. Establishing the Complete Trust Hierarchy
- IoT device as hardware oracle provides measured data to the blockchain. Due to its possible large amount, data can be recorded off-chain and the blockchain stores just a hash as proof of data content.
- Blockchain—as recommended in Table 1, the blockchain considered for metrology-related applications is in general private, ensuring who can have access to data and write to the blockchain. However, it is not excluded that one could use also a hybrid blockchain in cases when data owner (or generator) wants parts of the data to be publicly visible, or when the scope of users is very broad, e.g., in use-cases for supply chains with high number of participants. A consortium blockchain could be an option for the trust model that is administrated by more entities, e.g., for inter-NMI applications. Who can be a verifying blockchain node and the process of authorizing a node depends on the blockchain type, but in any case, it is administered by one entity (in private and hybrid blockchain) or more entities (in consortium blockchain). Consequently, public blockchain is more limited regarding the possible use-cases for IoT blockchain applications.
- Software oracle provides additional data about oracles, users and institutions, e.g., links to oracle datasheets, general information about a laboratory, and NMI.
- Inbound oracle provides data to smart contracts to institutions for sensor verification (smart contract 2). On the other side, it provides data to smart contracts for triggering sensor recalibration (smart contract 3).
- Outbound oracle provides data to authorized users (according to their access levels).
- Smart contract 1 provides the blockchain data about IoT device (hardware oracle) WELMEC compliance and possible tampering events, triggering corresponding events, e.g., rejection of data.
- Smart contract 2 triggers sensor (re)calibration based on inbound oracle, i.e., based on digital calibration certificate issued by institutions.
- Smart contract 3 triggers (re)certification procedure carried out by accreditation institution (issuing digital calibration certificate and recording it on a blockchain).
- Digital calibration certificate issued by an accreditation institution and recorded on a blockchain.
- The legal framework must be changed to legalize blockchain usage in metrology procedures.
- In order to be completely accepted and widely used, the blockchain-based trust concept in metrology must be legally mandatory. In contrast, i.e., just as an alternative in addition to the well-established tradition of the paperwork, the blockchain-based trust concept would not prevail due to the conservative nature of metrology.
- The concept, as well as its building blocks (for example, what kind of DCC format should be used) must be also adopted by the users. In doing so, the question remains of should the adoption be pushed top-down (i.e., starting from defined laws and regulations and applying them in practice) or bottom-up (i.e., waiting for which concept and elements will be accepted by the user community and then define laws and regulations also corresponding to user habits).
- Harmonization between the legal framework and technical capabilities (and limitations) of the blockchain, e.g., evaluating the content of smart contracts in comparison to the legal documents and resolving possible disputes in case of later identified discrepancies.
- Should such IoT devices as oracles communicate directly with the blockchain or should more IoT devices be connected to the internet via a gateway. In the first case, the IoT device is more costly due to its higher hardware and software complexity, but the lower number of communication intermediaries (gateways) in such kind of structure increases the data security.
- In terms of possible applications, data recorded on the blockchain contribute to the transparency and traceability, e.g., in supply chains, which raises trust in corresponding products and also their value. However, it is needed to further explore the possibilities for measured data itself to become a product, i.e., an object of trade in the data market. Additionally, in this case, the trust model is again very important, because more trust in the measured data means a higher price of the data as a product.
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
|IoT||Internet of Things|
|WELMEC||(Western) European Legal Metrology Cooperation|
|SI Units||International System of Units|
|FAIR+T||Findable, Accessible, Interoperable, Re-usable, and Traceable|
|IIoT||Industrial Internet of Things|
|DCC||digital calibration certificate|
|NMI||national metrology institute|
Appendix A. References Relevant to the State of the Art
|Blockchain in general (B)||[1,2,16,17,18,19,26,37,38]|
|IoT blockchain application (IB)||[10,11,12,27]|
|Oracle issue of blockchain (OB)||[3,23,25]|
|Metrology in general (M)||[4,5,22,28,33,44,47]|
|Digital transformation of metrology (TM)||[6,7,8,9,20,21,42,43]|
|Blockchain as possible infrastructure for digital transformation of metrology (BTM)||[13,14,15,24,45,46]|
|Miscellaneous||anti-tampering and security||[29,30,31,32,33]|
Appendix B. Blockchain Platforms and WELMEC Regulations
|L1. Completeness of measurement data stored||yes||yes|
|L2. Protection against accidental or unintentional changes||no||yes|
|L3. Integrity of data||yes||partial|
|L4. Traceability of stored measurement data||yes||yes|
|L5. Confidentiality of keys||yes||yes|
|L6. Retrieval, verification, and an indication of stored measurement data||yes||yes|
|L7. Automatic storing||no||no|
|L8. Storage capacity and continuity||yes||yes|
|T1. Completeness of transmitted data||yes||yes|
|T2. Protection against accidental or unintentional changes||no||yes|
|T3. Integrity of data||yes||partial|
|T4. Traceability of transmitted measurement data||yes||yes|
|T5. Confidentiality of keys||yes||yes|
|T6. Receiving, verification and handling of transmitted measurement data||yes||yes|
|T7. Availability of transmission services||yes||yes|
|T8. Transmission delay||yes||yes|
|S1. Realization of software separation||partial||partial|
|S2. Mixed indication||yes||yes|
|S3. Protective software interface||yes||yes|
|D1. Download mechanism||yes||yes|
|D2. Authentication of transmitted software||yes||yes|
|D3. Integrity of downloaded software||yes||yes|
|D4. Traceability of legally relevant software download||yes||yes|
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|Requirements for Digital Representation in Metrology Processes [5,9]||Blockchain Properties||Recommendations/Possible Issues|
|Contain all relevant information for conformity assessment, verification, market surveillance in a machine-readable way||Data comprised in transactions||The amount of data could be a problem. It is needed to use/store data in databases outside the blockchain|
|Contain all relevant information for customers to gain trust and confidence in the products and quality measures|
|Know the relevant standards and regulations, and provide machine-readable information about it||Blockchain uses machine-readable information only||It is necessary to make relevant standards and regulations also machine-readable|
|Provide machine-readable interfaces for users and manufacturers to enable “smart quality assurance”||-|
|Combine machine-readable documents and certificates, enable automation of digital QI processes|
|Be secured and validated to provide access to information only to eligible parties||Blockchain uses asymmetric cryptography to grant access to users||To limit who can have access, a private blockchain network is recommended [13,14,15]|
|Not requested, but it could be an additional benefit||Smart contracts embed terms and conditions of a contract between two or more parties [16,17,18]||Automated decision making and recording of the decision on the blockchain|
|Standard-Based Requirements (Scope of the Trust Model)|
|No link with legal requirements||Can be taken into account by the courts, e.g., WELMEC 7.2 Software Guide||Conformity is a guarantee, but not the only way that requirements have been met||Conformity required by law, e.g., ISO/IEC 17025—Testing and calibration laboratories||Law based on a standard||Laws independent on a standard, e.g., national metrology laws|
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Miličević, K.; Omrčen, L.; Kohler, M.; Lukić, I. Trust Model Concept for IoT Blockchain Applications as Part of the Digital Transformation of Metrology. Sensors 2022, 22, 4708. https://doi.org/10.3390/s22134708
Miličević K, Omrčen L, Kohler M, Lukić I. Trust Model Concept for IoT Blockchain Applications as Part of the Digital Transformation of Metrology. Sensors. 2022; 22(13):4708. https://doi.org/10.3390/s22134708Chicago/Turabian Style
Miličević, Kruno, Luka Omrčen, Mirko Kohler, and Ivica Lukić. 2022. "Trust Model Concept for IoT Blockchain Applications as Part of the Digital Transformation of Metrology" Sensors 22, no. 13: 4708. https://doi.org/10.3390/s22134708