TY - JOUR
T1 - Newton-interpolation-based zk-SNARK for Artificial Internet of Things
AU - Shang, Xinglin
AU - Tan, Liang
AU - Yu, Keping
AU - Zhang, Jing
AU - Kaur, Kuljeet
AU - Hassan, Mohammad Mehedi
N1 - Funding Information:
This work was supported by King Saud University , Riyadh, Saudi Arabia, under Researchers Supporting Project number RSP-2021/18 .
Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/12/1
Y1 - 2021/12/1
N2 - Artificial Internet of Things (AIoT) is that the system collects all kinds of information in real-time through various sensors, and intelligence analysis of the data through machine learning in the terminal equipment, edge domains, or cloud centers, including positioning, comparison, forecasting, scheduling, etc. which brings about the data security and privacy issues. The blockchain is a tamper-evident, unforgeable distributed ledger that protects security and privacy through the famous algorithm zk-SNARK, which is also widely used in virtual digital currencies such as Zcash. In addition, by using zk-SNARK technology in the Loopring DEX 3.0 in Ethereum, not only decentralization but also transaction performance can be guaranteed. However, there are three main problems of zk-SNARK, one is the need to guarantee calculation accuracy, two is the long time to generate evidence, especially when using Lagrangian interpolation to QAP the transaction data requires more computation; the last is the poor scalability, especially when nodes need to recalculate all data when adding new transactions. In this paper, we propose a modified zk-SNARK based on Newtonian interpolation, improve the QAP part of zk-SNARK by Newtonian interpolation, and verify the correctness of the scheme through instantiation. Finally, we analyze the computational efficiency of the two interpolation methods, and the results show that Newton interpolation solves the above two problems in the original zk-SNARK, and significantly reduces the time complexity of the algorithm, which can further promote the application of blockchain in data management of AIoT.
AB - Artificial Internet of Things (AIoT) is that the system collects all kinds of information in real-time through various sensors, and intelligence analysis of the data through machine learning in the terminal equipment, edge domains, or cloud centers, including positioning, comparison, forecasting, scheduling, etc. which brings about the data security and privacy issues. The blockchain is a tamper-evident, unforgeable distributed ledger that protects security and privacy through the famous algorithm zk-SNARK, which is also widely used in virtual digital currencies such as Zcash. In addition, by using zk-SNARK technology in the Loopring DEX 3.0 in Ethereum, not only decentralization but also transaction performance can be guaranteed. However, there are three main problems of zk-SNARK, one is the need to guarantee calculation accuracy, two is the long time to generate evidence, especially when using Lagrangian interpolation to QAP the transaction data requires more computation; the last is the poor scalability, especially when nodes need to recalculate all data when adding new transactions. In this paper, we propose a modified zk-SNARK based on Newtonian interpolation, improve the QAP part of zk-SNARK by Newtonian interpolation, and verify the correctness of the scheme through instantiation. Finally, we analyze the computational efficiency of the two interpolation methods, and the results show that Newton interpolation solves the above two problems in the original zk-SNARK, and significantly reduces the time complexity of the algorithm, which can further promote the application of blockchain in data management of AIoT.
KW - AIoT
KW - Blockchain
KW - Newton interpolation
KW - ZK-SNARK
KW - Zero knowledge proof
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U2 - 10.1016/j.adhoc.2021.102656
DO - 10.1016/j.adhoc.2021.102656
M3 - Article
AN - SCOPUS:85115329635
SN - 1570-8705
VL - 123
JO - Ad Hoc Networks
JF - Ad Hoc Networks
M1 - 102656
ER -