Data tampering avoidance for food supply chain traceability system using blockchain technology
Nowadays, the globalization of modern retail markets is increasing, and the supply chain from producers to end users is increasing and becoming more and more important. It is not uncommon to produce products in China, which is packaged in the Indonesia and sold in Thailand. This produces many arg...
Saved in:
| 主要作者: | |
|---|---|
| 格式: | Thesis |
| 語言: | English |
| 出版: |
2019
|
| 主題: | |
| 在線閱讀: | http://psasir.upm.edu.my/id/eprint/83869/1/FSKTM%202019%2042%20-%20IR.pdf |
| 標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
| 總結: | Nowadays, the globalization of modern retail markets is increasing, and the supply chain
from producers to end users is increasing and becoming more and more important. It is
not uncommon to produce products in China, which is packaged in the Indonesia and
sold in Thailand. This produces many arguments, for instance is when the product failed
to follow such guiding and any quality requirement. In these cases, it is vital to find
entities or people that affected by the catastrophe and not only focusing to find the cause
of the product failure. Therefore, companies must improve their ability to track products
from producers to end consumers by focusing data integrity issues in both parties. Advanced data secure tracking systems is one of the advantage available because they
provide effective response to product failures and reliable information for all
stakeholders in term of the data integrity. Therefore, this study proposed a blockchain
technology to be incorporated in the traditional traceability system to enhance the
security of data transaction by adapting the security technique in the blockchain to
increase the safety assurance of the data by having data tampering avoidance as one of
the integrity aspects. The blockchain algorithm will be used to link each data that been
inserted into the system to protect it from any attempt of data tampering such as
unauthorized data modification. The results showed that the algorithm was able to
preserve data integrity up to 100% accuracy. |
|---|