Sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc. Today, with the proliferation of small communication devices with sensors that collect environmental data, semantic Web technologies are becoming closely related with sensor networks. The linking of elements from Semantic Web technologies with sensor networks has been called Semantic Sensor Web and has among its main features the use of ontologies. One of the key challenges of using ontologies in sensor networks is to provide mechanisms to integrate and exchange knowledge from heterogeneous sources (that is, dealing with semantic heterogeneity). Ontology alignment is the process of bringing ontologies into mutual agreement by the automatic discovery of mappings between related concepts. This paper presents a system for ontology alignment in the Semantic Sensor Web which uses fuzzy logic techniques to combine similarity measures between entities of different ontologies. The proposed approach focuses on two key elements: the terminological similarity, which takes into account the linguistic and semantic information of the context of the entity’s names, and the structural similarity, based on both the internal and relational structure of the concepts. This work has been validated using sensor network ontologies and the Ontology Alignment Evaluation Initiative (OAEI) tests. The results show that the proposed techniques outperform previous approaches in terms of precision and recall.

The growth of the Internet of Things (IoT) has favored the emergence of new applications and services. Consequently, new challenges in data security and protection have arisen because many IoT systems collect sensitive data that could be the target of attacks and intrusion attempts. Such is the case of smart toy platforms, where the loss of personal data is particularly serious because it involves children and therefore user privacy requires special protection. In this paper, we propose a series of security mechanisms to protect an IoT smart toy platform designed to help child development professionals in the early detection of psychomotor delays. Protecting information is crucially important in this environment, as a successful attack could be used to extract personal and health-related information. We have designed and built specific security mechanisms for the system by identifying the main threats in each submodule of the system, and then neutralizing or minimizing them. Due to the smart toys’ hardware restrictions, a specific encryption and authentication mechanism is proposed and presented here. All the mechanisms have been validated on the platform, and have proved to be a feasible and secure solution for this sensitive environment.

In this paper, we describe the design considerations and implementation of a smart toy system, a technology for supporting the automatic recording and analysis for detecting developmental delays recognition when children play using the smart toy. To achieve this goal, we take advantage of the current commercial sensor features (reliability, low consumption, easy integration, etc.) to develop a series of sensor-based low-cost devices. Specifically, our prototype system consists of a tower of cubes augmented with wireless sensing capabilities and a mobile computing platform that collect the information sent from the cubes allowing the later analysis by childhood development professionals in order to verify a normal behaviour or to detect a potential disorder. This paper presents the requirements of the toy and discusses our choices in toy design, technology used, selected sensors, process to gather data from the sensors and generate information that will help in the decision-making and communication of the information to the collector system. In addition, we also describe the play activities the system supports.

TLS is an essential building block for virtual private networks. A critical aspect for the security of TLS dialogs is authentication and key exchange, usually performed by means of certificates. An insecure key exchange can lead to a man-in-the-middle attack (MITM). Trust in certificates is generally achieved using Public Key Infrastructures (PKIs), which employ trusted certificate authorities (CAs) to establish certificate validity chains.