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With the increasing value of various kinds of data in the era of big data, the demand of different subjects for data transactions has become more and more urgent. In this paper, a blockchain-based data transaction protection scheme is proposed to realize the secure transaction sharing among data. This paper carries out the following work: by analyzing the existing data transaction models, we find the data security and transaction protection problems, establish a third-party-free data transaction platform using blockchain, protect users’ data security by combining AES and improved homomorphic encryption technology, and upload the encrypted data to the Interplanetary File System (IPFS) for distributed storage. Finally, we use the powerful functions of the IPFS, combined with inadvertent transmission protocol, two-way authentication, zero-knowledge proof, and other security verification for data transactions. The security analysis proves that this scheme has higher security despite the time overhead, and we will continue to optimize the scheme to improve efficiency in the future.

This paper focuses on the scalability problems for high-speed switches, and presents an integrated scheduling algorithm that supports unicast and multicast traffic efficiently in input-queued packet switches. Considering the tradeoff balancing complexity and performance, the proposed integrated algorithm performs without iteration, and reduces the scheduling overhead to O(N) with a two-phase (request-grant) sequential scheduling for unicast and multicast traffic. In addition, it can be implemented in a fully distributed way, which is more suitable for high-speed switches. Simulation results show that the proposed algorithm exhibits a good performance in terms of throughput and average delay, at different traffic compositions under various traffic patterns