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Network Science and Engineering Group

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3108 Engineering Hall
1701D Platt St.
Manhattan, KS 66506
785-532-5600
Fax: 785-532-1188

Hours: 8 am-12pm, 1pm-5pm M-F

Decentralized blockchain-based provenance tracking system

A blockchain based framework will be designed to: 1) Decentralize cattle farm databases, 2) Protect the integrity of the data, 3) Provide traceability features in order identify sources of infection during disease outbreaks. The cattle industry data has a nature of confidentiality due to competing business and the fact that uncensored data could hurt ones profit. Hence, this project provides a method to get the proof of data integrity from the blockchain without actually exposing the data to unwanted eyes.

 

blockchain framework

Figure: A blockchain-based framework for beef cattle supply chains.

Distributed ledgers using blockchain have gained traction in the supply chain industry due to their unique features of immutability and transparency. They have given people the abilities to solve business problems which were impossible using traditional systems. The US beef cattle industry lacks adequate traceability as most of the farm owners consider such data confidential; possibly harming their businesses if exposed. This article attempts to solve this problem by proposing a smart contract-based supply chain framework using a permissioned blockchain network. This system supports anonymity for the users to protect identities and lets every user store their data locally, while ensuring that the changes are recorded in the chain with cryptographic proofs (hashes). The proposed framework also has methods for the users to perform business transactions and transfer animal-related data to new owners as required. In addition to that, smart contracts have been added to conduct anonymous surveys for data aggregation. The technical contribution of this article is in the system design on how users, data, and communications are handled to maintain data ownership and user privacy while ensuring immutability and confidentiality at different levels of data aggregation. This article also contains an evaluation of the system using integration tests where the outcomes meet the expected design requirements. The framework can be applied to the US beef cattle industry as well as other supply chains with minimal modifications.

 

Duration: January 1, 2019 - May 31, 2021

Investigators

Faculty

Caterina Scoglio (Google Profile)

Don Gruenbacher

David Amrine

PhD Student

Tanvir Ferdousi

Graduate Student

Divya Vani Lakkireddy

Thomas Mallinson

Undergraduate Student

Jacob Swift

Publications

T. Ferdousi, D. Gruenbacher, C. Scoglio (2020), "A permissioned distributed ledger for farm animal supply chains".

 


 

Supported by the Global Food Systems Seed Grant Program, at Kansas State University. Any opinions, findings, and conclusions or recommendations expressed in this website are those of the authors.