A distributed charging system based on the Internet of Things can provide important supports to ensure the safe and sustainable operation of electric vehicles (EVs). Usually, drivers prefer to use local charging piles by querying the remote cloud server. Frequent communication with the cloud server will not only produce an unnecessary communication overhead but also increase the latency of response. More seriously, the cloud-based centralized management mode is vulnerable to cyber-attacks, which usually leads to privacy leakage. However, previous studies seldom focus on the privacy issue of the charging system for EVs. In this article, a decentralized and privacy-preserving charging scheme for EVs is proposed, which is based on blockchain and fog computing. In this scheme, fog computing is introduced to provide local computing with low latency. Specifically, a fog computing network, which is composed of fog computing nodes (FCNs), is used to provide localized services. Besides, a flexible consortium blockchain architecture is proposed. The blockchain system is deployed on the distributed FCNs, providing a decentralized and secure storage environment. By combining mutual authentication, smart contract, and blockchain-based storage, the security of privacy in the charging process can be ensured. The theoretical analysis and experiments demonstrate the advantages of the proposed scheme.

With the rapid development of information technology, logistics systems are developing towards intelligence. The Internet of Things (IoT) devices throughout the logistics network could provide strong support for smart logistics. However, due to the limited computing and storage resources of IoT devices, logistics data with user sensitive information are generally stored in a centralized cloud center, which could easily cause privacy leakage. In this paper, we propose Logisticschain, a blockchain-based secure storage scheme for logistics data. In this scheme, the sensing data from IoT devices should be encrypted for fine-grained access control, and a customized blockchain structure is proposed to improve the storage efficiency of systems. Also, an efficient consensus mechanism is introduced to improve the efficiency of the consensus process in the blockchain. Specific to the logistics process, the sensing data generated from IoT devices will be encrypted and aggregated into the blockchain to ensure data security. Moreover, the stored logistics records can be securely audited by leveraging the blockchain network; both IoT data and logistics demands cannot be deleted or tampered to avoid disputes. Finally, we analyze the security and privacy properties of our Logisticschain and evaluate its performance in terms of computational costs by developing an experimental platform.

Nowadays, recommender systems are used widely in various fields to solve the problem of information overload. Collaborative filtering and content-based are representative solutions in recommender systems, however, the content-based model has some shortcomings, such as single kind of recommendation results, lack of effective perception of user preferences; while, for the collaborative filtering model, there is a cold start problem, and such a model is greatly affected by its adopted clustering algorithm. To address these issues, a hybrid recommendation scheme is proposed in this article, which is based on both collaborative filtering and content-based. In this scheme, we propose the concept of time impact factor, and a time-aware user preference model is built based on it. Also, user feedback on recommendation items is utilized to improve the accuracy of our proposed recommendation model. Finally, the proposed hybrid model combines the results of content recommendation and collaborative filtering based on the logistic regression algorithm.