Automatically Generate ELearning Quizzes from IoT Security Ontology The InternetofThings is a network platform which provides service to physical world by connecting electronic devices, processing and analyzing data. Meanwhile, such fragile connectivity, low security awareness and the lack of knowledge of users can lead IoT devices to be the target of some attackers and then becomes insecurity of things. To solve that problem, in this research, we aim to build an Elearning system which is based on Ontology method to educate users in order to improve their security awareness. Basically, our system mainly consists of three steps. Firstly, we classified, analyzed and characterized the concepts of IoT security domain. Then we built an IoT security Ontology based on the output of classification and analysis. Finally, we developed a java program to implement the function of automatically generate Multiple Choice Questions based on IoT security Ontology descriptions. In this research, we made Elearning materials by extracting and rearranging useful knowledge from on results of classification and analysis. And using a Moodle as eLearning platform, we upload those learning materials and all the outputs from our system to Moodle and utilized Moodle to create courses and quizzes in order to let user study through our system.

Lightweight DataSecurity Ontology for IoT Although current estimates depict steady growth in Internet of Things (IoT), many works portray an as yet immature technology in terms of security. Attacks using 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 and challenges, like data markets, aggregators, processors and search engines, which rise the need for security. New regulations, such as GDPR , also call for novel approaches on datasecurity, covering personal data. In this work, we present DS4IoT, a datasecurity ontology for IoT, which covers the representation of datasecurity concepts with the novel approach of doing so from the perspective of data and introducing some new concepts such as regulations, certifications and provenance, to classical concepts such as access control methods and authentication mechanisms. In the process we followed ontological methodologies, as well as semantic web best practices, resulting in an ontology to serve as a common vocabulary for data annotation that not only distinguishes itself from previous works by its bottomup approach, but covers new, current and interesting concepts of datasecurity, favouring implicit over explicit knowledge representation. Finally, this work is validated by proof of concept, by mapping the DS4IoT ontology to the NGSILD data model, in the frame of the IoTCrawler EU project.