Logistics companies are increasingly adopting private blockchains for enhanced data management because of the trends in cooperation. Nevertheless, this practice poses new challenges concerning the security and sharing of data. The real-time nature and diversity of logistics data increase the difficulty of protecting the data. Additionally, when transportation information changes, downstream enterprises must promptly adjust their production plans to accommodate these alterations. The strict access controls of private blockchains can obstruct downstream enterprises from obtaining data, posing a challenge to the overall operational efficiency. In this paper, we propose an innovative logistics data protection scheme that employs private set intersection (PSI) and blockchain cross-chain technology to achieve data security. In our scheme, logistics companies within the logistics consortium are added as trusted agents to the public blockchain, enabling downstream enterprises to acquire logistics data integration from the public blockchain. Utilizing an RSA-based PSI protocol, our approach enhances exchange efficiency while protecting private data without transmitting additional information. We evaluate the performance of the proposed solution through a series of experiments, and the results demonstrate that our solution can achieve secure and efficient logistics data exchange.

Game recommendation algorithms can help users narrow down their search and find games of interest. The mainstream game recommendation algorithms currently are collaborative filtering game recommendation algorithms. However, collaborative filtering mainly relies on user ratings and similarity to make recommendations. When user data includes a substantial amount of social information, this method fails to analyze the users' social data comprehensively. It cannot grasp the users' attitudes, opinions, and emotions, leading to inaccurate recommendation results. In this paper, we propose a hybrid recommendation model. In this model, we combine collaborative filtering algorithms with sentiment analysis, taking both users' gaming data and social data into account within the hybrid model. After selecting the most appropriate K value, we use the KNN classification algorithm for personalized recommendations, optimizing the user-based collaborative filtering game recommendation algorithm. The evaluation of the recommendation results is derived from MSE, Accuracy, F1, Precision, and Recall. The results indicate that the recommendation algorithm, after hybridization, shows an improvement in recommendation accuracy compared to the user-based collaborative filtering game recommendation algorithm, proving the effectiveness of this research.

Blockchain database has been widely applied in various fields, providing a secure architecture for data storage and sharing. In blockchain databases, the use of sharding technology can enhance the system’s scalability and improve transactions in the network to be processed in parallel. However, when applying searchable encryption techniques to query encrypted data in sharding blockchains, frequent data access to different shards results in uneven load distribution, leading to hotspot issues and reducing system efficiency. To tackle the challenge, we present SDB, a scheme integrating searchable encryption with sharding technology to enhance the scalability of blockchain databases. Firstly, we introduce a two-stage sharding mechanism. It performs pre-sharding based on keywords, and then implements fine-grained dynamic adjustments through improved jump consistent hashing, effectively resolving the load imbalance problem. Secondly, we present a cross-shard query strategy based on encrypted indexes, which constructs verifiable indexes for encrypted data and converts user queries into a multiway query tree. This addresses the cross-shard query optimization problem in encrypted environments. Under the experiment and security analysis, SDB achieves efficient cross-shard queries with higher query performance and throughput, at least 30% and 20% higher than state-of-the-art scalable blockchain database schemes.