PROJECT TITLE :

SIGNORA: A Blockchain-Based Framework for Dataflow Integrity Provisioning in an Untrusted Data Pipeline

ABSTRACT:

The dataflow of a typical data pipeline begins at the first node of the pipeline, which is where the data are first started, and continues all the way to the last node of the pipeline, which is where the processed data will be stored. Protecting the pipeline's dataflow integrity is absolutely necessary in light of the staggering number of participants involved in the process. Previous studies have presented potential solutions to this problem; however, the problem of how to deal with an untrusted data pipeline has not yet been investigated, which is what inspired us to come up with the SIGNORA solution. In order to ensure the integrity of the dataflow, our solution combines the ideas of blockchain receipts and chains of digitally signed transactions. A non-repudiation guarantee is provided by the chain of signatures, and a non-tampering guarantee is provided by blockchain receipt thanks to the hash of the data and signatures that is anchored in the blockchain. Aside from that, SIGNORA satisfies essential requirements of running data pipeline processing in an open and untrusted environment, such as I providing reliable identity management, (ii) solving the trust and accountability issues through a reputation system, (iii) supporting various devices through multiple cryptographic algorithms (i.e., ECDSA, EdDSA, RSA, and HMAC), and (iv) off-chain processing. These are just some of the essential requirements that SIGNORA The findings of our experiments indicate that SIGNORA is capable of providing dataflow integrity provisioning in a variety of settings involving the size of the data payload with a reasonable amount of overhead. In addition, the cost of smart contract methods has been analyzed, and numerous off-chain solutions have been investigated to address the issue of lowering the costs of transactions. Last but not least, the reputation system is able to adjust to the past actions of nodes by raising their scores when they actively engage in ethical behavior and lowering their scores when they become inactive for an extended period of time. As a result, SIGNORA is able to provide a high degree of accountability for participants working together in an environment where there is a lack of trust.