Owing to the attractive properties of decentralization, unforgeability, transparency, and traceability, blockchain is increasingly being used in various scenarios such as supply chain and public services, where massive Spatial-Temporal-Keywords (STK) transactions need to be packaged to the blockchain systems. However, due to the multi-dimensionality of STK transactions and transaction randomness among different blocks, existing solutions fail to enable queries in a verifiable and efficient way for blockchains storing multidimensional transactions. To this end, this paper takes the first step to innovatively propose an authenticated and efficient query approach in hybrid blockchain systems consisting of on-chain and off-chain parts. We first design a new data structure named MRK-Tree in the block body, which organizes STK transactions for efficient nodes pruning of both kNN and range queries. Then we propose an improved block header, which improves the efficient pruning of blocks on the basis of ensuring the authentication of query results. Also, we design a cross-block searching algorithm named Efficient Block Pruning (EBP) and intra-block searching algorithms named Authenticated kNN/Range Query (AKQ/ARQ) to accelerate authenticated queries for multiple MRK-Trees in the hybrid blockchain systems. Authentication mechanisms are proposed to ensure the soundness and completeness of query results. Rigorous security analysis validates the practicability of the proposed approach. We build a blockchain prototype to comprehensively evaluate the performance of proposed query schemes. Extensive evaluation results with real datasets reveal that our approach can ensure authenticated queries, meanwhile improving the time efficiency by up to 36.45x and space efficiency by up to 4 orders of magnitude compared with the well-known benchmark query schemes.

The sharing of electronic healthcare records (EHRs) is important to healthcare and medical research. However, institutions are faced with difficulties in privacy protection and efficiently secure data exchange. The main objective of this study is to propose a controllable secure blockchain-based EHRs sharing scheme. For this purpose, blockchain technologies are combined with interplanetary file systems (IPFS) to provide efficient secure EHRs sharing. Firstly, the IPFS-based EHR file system (IEFS) is designed to save and share large-size EHR files among medical institutions. With the high-throughput content-addressed block storage model and appropriate redundant backup of IPFS, IEFS is tamper-resistant and free of a single point of failure. Secondly, the blockchain is used to implement the blockchain-based EHR abstract system (BEAS) to manipulate EHR abstracts access. In BEAS, the EHR file addresses generated by IEFS are encrypted and saved in EHR abstracts for privacy protection. Since EHR abstracts are encrypted by patients’ public keys, the sharing of EHR files is under the control of patients. In our experiment, a prototype system is developed to validate the proposed scheme. The experimental results showed that (1) EHRs are securely shared under the control of patients and (2) EHR files are retrieved at an acceptable speed supported by IPFS technology. In this paper, solutions to some important practical issues such as incapacitated patients, encryption key forgetting/missing, and efficient interaction of doctors with EHRs sharing scheme are also seriously discussed.

E-Auction improves the efficiency of bid transaction. However, the protection of bidders’ privacy, transaction fairness and verifiability, transaction data security, high cost of third-party auction center, and other issues have attracted more attention. According to the transaction process and basic principles of the sealed auction, we explored the problems existing in the current sealed-bid e-auction schemes. Based on the blockchain technology, we proposed a sealed-bid e-auction scheme with smart contract technology, Bulletproofs zero-knowledge proof protocols, and Pedersen commitment algorithm. The proposed scheme constructed an auction mechanism without the third-party auctioneer so as to restrict the behaviors of auction parties for the sake of auction security, reliability, fairness, and privacy protection. Compared with the related sealed e-auction schemes based on blockchain technologies in six metrics, we conducted the experiment to show that the proposed scheme protected the bid information from leakage well and successfully verified the winning bid price and the related bidder by all transaction participants without the third-party auctioneer.

The rapid development of the blockchain leads to a blowout of on-chain transactions, contracts, and currencies, which will further accelerate the increase of data. The existing blockchain systems typically support exact transaction queries, which, however, cannot satisfy the QoS requirements with intelligent adjustment in the blockchain systems. To this end, this paper takes the first step to define and address the practically important problem of transaction cardinality estimation for QoS-adjustable intelligent blockchain systems. We first establish a mathematical relationship between the bit string and transaction cardinality. Thus, we can leverage the number of leading 1s of the obtained bit string to estimate the transaction cardinality. We then improve the block header and body with a corresponding search algorithm to access bit strings in blocks. We also propose an estimation protocol with intelligent adjustable QoS to support accuracy-guaranteed and efficiency-optimized estimation. Finally, we design an authentication scheme and guarantee the reliability of our protocol through rigorous theoretical derivation. When achieving the transaction cardinality estimation in blockchain, two technical challenges need to be addressed. (i) To ensure efficient, verifiable, and overhead-saving bit string accessing mechanism in blockchain, we propose the Merkle Cardinality Tree (MCT) and target block filtering mechanism based on Bloom Filter (BF) in off-chain and improve on-chain block header by joining the abstract of MCT and BF. (ii) To improve estimation efficiency while guaranteeing accuracy requirements in hybrid blockchain scheme, we propose a Dynamic One-round Sampling-based cardinality Estimation (DOSE) protocol and integrate BF-DOSE to intelligently accelerate estimation. We build MCT in Ethereum and store the MCT Root in the block header for estimation authentication. Extensive experiments reveal that our BF-DOSE protocol can well satisfy various accuracy and efficiency requirements of QoS-adjustable intelligent blockchain systems, and is one to two orders of magnitude faster compared with benchmark schemes.

Tag inventory is one of the most fundamental tasks for RFID systems. However, the Framed Slotted Aloha (FSA) protocol specified in C1G2 standard is of low time-efficiency, because it needs to collect all tags in the system. To improve time-efficiency, research communities proposed a batch of sampling-based approaches, in which the reader only needs to collect a small set of sampled tags instead of all. Although time-efficiency has been improved, existing sampling-based approaches still have two common limitations. First, all tags in the system are assumed to have the same sampling probability. It is unfair that tags attached to differential items (e.g., different values) have the same chance to be sampled and collected. Second, all existing sampling-based approaches stay in theory level and cannot be deployed on Commercial Off-The-Shelf (COTS) RFID devices, because the C1G2 standard does not support the sampling function at all. To deal with the above two limitations, this paper studies the new problem of differential tag sampling-letting each RFID tag be identified with a given sampling probability. In this paper, we use the COTS RFID devices including Impinj Speedway R420 reader and Monza 4QT tags to implement the Differential Tag Sampling (DTS) operation. Then, we apply probabilistic analytics on the collected tag data to address some practically important problems such as Multi-category Tag Cardinality Estimation (MTCE), and Value-based Missing Tag Detection (VMTD). Although the analytics results are not 100% accurate, the deviation in the results can be controlled below a small threshold and DTS can significantly improve the time-efficiency. DTS can be easily deployed on the COTS RFID systems, because it is totally compliant with the C1G2 standard. Extensive experiments demonstrate that DTS is able to let each tag take the given sampling probability to be sampled and identified. Moreover, the proposed DTS protocol can significantly reduce the execution time of MTCE and VMTD by nearly 70% than the FSA protocol.