No abstract

Through three development routes of authentication, communication, and computing, the Internet of Things (IoT) has become a variety of innovative integrated solutions for specific applications. However, due to the openness, extensiveness and resource constraints of IoT, each layer of the three-tier IoT architecture suffers from a variety of security threats. In this work, we systematically review the particularity and complexity of IoT security protection, and then find that Artificial Intelligence (AI) methods such as Machine Learning (ML) and Deep Learning (DL) can provide new powerful capabilities to meet the security requirements of IoT. We analyze the technical feasibility of AI in solving IoT security problems and summarize a general process of AI solutions for IoT security. For four serious IoT security threats: device authentication, Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks defense, intrusion detection and malware detection, we summarize representative AI solutions and compare the different algorithms and technologies used by various solutions. It should be noted that although AI provides many new capabilities for the security protection of IoT, it also brings new potential challenges and possible negative effects to IoT in terms of data, algorithm and architecture. In the future, how to solve these challenges can serve as potential research directions.INDEX TERMS Artificial intelligence, deep learning, Internet of Things, machine learning, security.

The posterior ridge preservation technique using DBBM-C covered with a NBCM is a valid approach reducing the amount of the radiographic loss in alveolar ridge dimensions.

The immobilization of functional proteins onto solid supports using affinity tags is an attractive approach in recent development of protein microarray technologies. Among the commonly used fusion protein tags, glutathione S-transferase (GST) proteins have been indispensable tools for protein-protein interaction studies and have extensive applications in recombinant protein purification and reversible protein immobilization. Here, by utilizing pyrimidine-based small-molecule probes with a sulfonyl fluoride reactive group, we report a novel and general approach for site-selective immobilization of Schistosoma japonicum GST (sjGST) fusion proteins through irreversible and specific covalent modification of the tyrosine-111 residue of the sjGST tag. As demonstrated by sjGST-tagged eGFP and sjGST-tagged kinase activity assays, this immobilization approach offers the advantages of high immobilization efficiency and excellent retention of protein structure and activity.