A Framework for Automatically Generating IoT Security Quizzes in 360VR Images/Videos Based on Linked Data

Wei Shi, Tianhao Gao, Srishti Kulshrestha, Ranjan Bose, Akira Haga, Yoshihiro Okada

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Scopus citations

Abstract

Internet of Things (IoT) technology has greatly developed in the past ten years. Many smart buildings and smart homes are constructed and used. Because of the popularity of smart buildings and smart homes, the security problem becomes more and more important. How to effectively enhance people’s IoT security knowledge is discussed frequently. In the past, we have already developed a framework that can automatically generate the IoT quizzes based on Linked Data in a virtual 3D environment. In this paper, we discuss how to extend it to support the quiz generation using the images and/or videos captured by a 360-degree camera. In this paper, we will apply the object recognition technology to automatically find out the IoT devices from these images and videos. According to the recognizing result, our framework will generate related questions for test or train learners.

Original languageEnglish
Title of host publicationLecture Notes on Data Engineering and Communications Technologies
PublisherSpringer Science and Business Media Deutschland GmbH
Pages259-267
Number of pages9
DOIs
StatePublished - 2020
Externally publishedYes

Publication series

NameLecture Notes on Data Engineering and Communications Technologies
Volume47
ISSN (Print)2367-4512
ISSN (Electronic)2367-4520

Funding

Acknowledgments. The is research was mainly supported by Strategic International Research Cooperative Program, Japan Science and Technology Agency (JST) regarding “Security in the Internet of Things Space”, and partially supported by JSPS KAKENHI Grant Number JP16H02923 and JP17H00773.

FundersFunder number
Japan Society for the Promotion of Science17H00773, JP16H02923
Japan Society for the Promotion of Science
Japan Science and Technology Agency
Strategic International Collaborative Research Program

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