Currently, the Internet of Things (IoT) is in a premature phase. Although it is growing at a steady pace, there is still a need for further research in the field of security. Attacks on low-performance devices, the application of new technologies, and data analysis to infer private data, lack of development in some aspects of security offer a wide field for improvement. The advent of semantic technologies for IoT offers a new set of possibilities. However, this comes with challenges in data markets, aggregators, processors, and search engines, which raise the need for security. New regulations also call for novel approaches on data security, covering personal data, and a way of describing different data security traits involved in data access from an IoT system perspective.

Many security ontologies, such as defense against money laundering (DAML), STAC (Security Toolbox: Attack & Countermeasure), IoT security (IoTSec), IoT Context-Based Security Evaluation (IoTSecEv), and IoT Privacy (IoT-Priv), have already been developed in different contexts. They have been selected due to some interest in applying these security ontologies in certain domains directly or indirectly based on IoT. However, it is still a challenge to describe the data security aspects that affect IoT systems. The foundation of this problem might be a rich set of use cases from which very specific data security description needs stemmed. More precisely, there is a need for further research in the field to provide some techniques addressing the following issues: (1) how to construct security ontology for meeting the requirements of exchanging data security in different application scenarios; (2) how to represent the data security aspects of data in search engines; (3) how to express data-security requirements to information providers.

The aim of this Special Issue is to bring together original research and review articles on semantic technology and security within IoT. This Special Issue explores recent advancements in semantic techniques (e.g., ontology, ontology matching technique, semantic web reasoning language (SWRL), etc). We particularly welcome submissions discussing information security knowledge-sharing models. Moreover, submissions including an effective way of performing filtering and ranking based on security traits of the data source are welcome. In addition, research discussing how to retrieve information from the source is also welcome. Finally, this Special Issue welcomes research discussing how to integrate the heterogeneous security ontologies among different platforms and any third parties to ease the access and handling of data.

Potential topics include but are not limited to the following:

• Construction of data-driven information security ontology in IoT
• Semantic enquiry technique on data markets and search engines in IoT
• Information security ontology matching technique in IoT and linked data cloud
• Semantic security data annotation and integration in IoT
• Artificial intelligence-enabled security in IoT