The exponentially increasing number of IoT devices makes the unlicensed industrial, scientific, and medical (ISM) radio bands (e.g., 2.4 GHz) extremely crowded. Currently, there is no efficient solution to coordinate the large amount heterogeneous IoT devices that have different communication technologies (e.g., WiFi and ZigBee). To fill this gap, in this paper, we introduce embedded multiple flows (EMF) communication method, which (i) embeds different pieces of information in existing traffic and (ii)concurrently sends out these information from one IoT sender to multiple IoT receivers that have a different communication technology from the sender. By doing this, our EMF method (i) enables cross-technology communication among heterogeneous IoT devices, (ii) does not introduce any extra control traffic, and (iii) is transparent to the higher layer applications. Our approach is implemented on USRPs and commercial off-the-shelf (COTS) ZigBee devices. We also conducted extensive experiments to evaluate our approach in real-world settings. The evaluation results show that EMF's throughput is more than 14 times higher than the latest cross-technology communication technique (i.e. FreeBee[1]).

In recent years, counterfeit luxury products have become a major concern for consumers worldwide. The reason for the proliferation of counterfeit products is that the manufacturing and distribution process is not transparent to consumers and this information can be easily falsified or altered by others. To solve this problem, this paper proposes the development of a management system using blockchain and smart contract technology to solve the problems of data forgery and data tampering, while tracking the information related to luxury products and ensuring the accuracy and authenticity of the relevant data, to achieve the purpose of luxury product anti-counterfeiting. When using Hyperledger Fabric to deploy the blockchain and execute smart contracts, all information related to the production and logistics process of luxury goods will be uploaded to the blockchain. No human intervention is required to create a complete, traceable, tamper-proof, and trusted repository. Compared to previous work, this paper combines blockchain technology with specific processes in the supply chain, employing a variety of security methods to secure the communication process. Moreover, our proposed solution is more flexible in transmission, with more secure protocols also making data harder to tamper with and falsify, thereby solving the problem of forgery and tracking of luxury products.

Network traffic classification based on machine learning is an important branch of pattern recognition in computer science. It is a key technology for dynamic intelligent network management and enhanced network controllability. However, the traffic classification methods still facing severe challenges: The optimal set of features is difficult to determine. The classification method is highly dependent on the effective characteristic combination. Meanwhile, it is also important to balance the experience risk and generalization ability of the classifier. In this paper, an improved network traffic classification model based on a support vector machine is proposed. First, a filter-wrapper hybrid feature selection method is proposed to solve the false deletion of combined features caused by a traditional feature selection method. Second, to balance the empirical risk and generalization ability of support vector machine (SVM) traffic classification model, an improved parameter optimization algorithm is proposed. The algorithm can dynamically adjust the quadratic search area, reduce the density of quadratic mesh generation, improve the search efficiency of the algorithm, and prevent the over-fitting while optimizing the parameters. The experiments show that the improved traffic classification model achieves higher classification accuracy, lower dimension and shorter elapsed time and performs significantly better than traditional SVM and the other three typical supervised ML algorithms.

In recent years, blockchain-related technologies and applications have gradually emerged. Blockchain technology is essentially a decentralized database maintained by the collective, and it is now widely applied in various fields. At the same time, with the growth of medical technology, medical information is becoming increasingly important in terms of patient identity background, medical payment records, and medical history. Medical information can be the most private information about a person, but due to issues such as operation errors within the network or a hacking attack by a malicious person, there have been major leaks of sensitive personal information in the past. In any case, this has become an issue worth studying to ensure the privacy of patients and protect these medical materials. On the other hand, under the current medical system, the patient’s EMR (electronic medical record) cannot be searched across the hospital. When the patient attends the hospital for treatment, repeated examinations will occur, resulting in a waste of medical resources. Therefore, we propose a blockchain-based secure inter-hospital EMR sharing system in this article. Through the programmatic authorization mechanism by smart contracts, the security of EMR is guaranteed. In addition to the essential mutual authentication, the proposed scheme also provides and guarantees data integrity, nonrepudiation, user untraceability, forward and backward secrecy, and resistance to replay attack.