Transparent Data Query in HCN

Data query enables a data user to quickly find and retrieve data according to the user-specified keywords, range, or other query metrics. Data query plays a vital role in supporting many data-intensive applications in future networks. As data are generated and distributed at heterogeneous network entities, data query is often conducted by a third party that is out of the trust domain of the query user. In this chapter, we investigate transparent data query services for HCN. First, we identify the necessity for transparent VNF query and slice configuration across different network resource providers and propose a blockchain-based verifiable query scheme for NFV-enabled network management. Second, we integrate SNARG-based on/off-chain computation model to achieve succinct storage of a query dictionary and efficient verifications of query results. At the same time, we further investigate the random access memory (RAM) issue of SNARG-based solution that causes inefficient proving overheads. To address the efficiency challenge, we design a two-level SNARG system that conducts a key query to reduce search space for a full query. From pre-computed authenticators and a Merkle tree, we design a dictionary pruning scheme to efficiently generate an aggregated authenticator for the verifications in the SNARG system for the full query. We analyze the security properties of each component in the proposed scheme to achieve verifiable data query on the blockchain. We conduct extensive experiments with a consortium network to demonstrate the on/off-chain efficiency of the proposed scheme. With our proposed dictionary pruning strategy, off-chain proof generation overheads can be significantly reduced.