Special Issue "Human-Centered Computing and Information Security: Recent Advances & Intelligent Applications"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: 31 December 2019.

Special Issue Editor

Guest Editor
Prof. Dr. Jong Hyuk Park Website E-Mail
Department of Computer Science and Engineering, Seoul National University of Science and Technology, (SeoulTech) Seoul 01811, Korea
Phone: +82-1090364042
Interests: IoT; human-centric computing; block-chain; information security; cloud computing

Special Issue Information

Dear Colleagues,

In recent years, human-centered computing (HC) has become most promising research domain in both industrial and academic areas worldwide. As a convergence of multiple disciplines, HC supports the effective bridging of various human-related computational elements, the physical world, and cyberspace. HC enables the design and development of an effective computer system that considers cultural, social, and personal aspects and mitigates issues such as human–computer interaction, human information interaction, information design, human–human interaction, and the relationship among art, social, cultural issues, and computing technologies. Using intelligent HC techniques, an organization or enterprise can design and develop several human–computer applications conveniently and economically to fulfill the critical functional or nonfunctional computational requisites from a set of users. However, it is critical for manufacturers of human–computer applications to implement common functions for security, data management, and communication. For instance, HC platforms (e.g., human-centered activities in multimedia, human-centered activities in IoT, human-centered activities in Blockchain) are implemented with individual security architectures, policies, goals, and have their own vulnerabilities and attack surfaces. Moreover, vulnerable computing resources in HC can be infected with malware and subsequently turned into a large botnet that further results in devastating DDoS attacks. Though information security is a serious and demanding factor of HC deployment, it is too often ignored in the design and development of HC oriented systems. Consequently, the provision of information security has been gathering much attention in all HC-related areas.

The aim of this Special Issue is to identify the emerging information security challenges in all HC-related areas. It will consist of up-to-date, state-of-the-art research contributions with novel design and developments of intelligent application, perception, and security methods in the HCC, to enhance the reliability and feasibility of HC in real-world applications.  

Topics of interest may include but are not limited to the following:

  • Big-data analysis and datamining for HC;
  • Internet of Things and Blockchain for HC;
  • AI and soft computing for HC;
  • Social computing and social intelligence for HC;
  • HC-based cloud, fog, and edge computing;
  • HC-based smart home and smart city;
  • Human–computer interaction and user-centered design;
  • Design and development of a secure human–computer applications;
  • Design and development of deep learning framework for HC services;
  • Study of human aspects of information security in HC;
  • Blockchain in HC;
  • Security and privacy for secure HC;
  • Trust management in an HC environment;
  • Efficient and secure HC applications for IoT;
  • Security and credibility verification in HC;
  • Intelligent and secure data processing in HC.

Prof. Dr. Jong Hyuk Park
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Human-centered computing 
  • Deep learning 
  • Artificial intelligence 
  • Internet of Things 
  • Smart city
  • Information security 
  • Blockchain 
  • Privacy

Published Papers (2 papers)

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Research

Open AccessArticle
An Identity Model for Providing Inclusive Services and Applications
Appl. Sci. 2019, 9(18), 3813; https://doi.org/10.3390/app9183813 - 11 Sep 2019
Abstract
Information and Communication Technologies (ICT) need to be accessible for every single person in the globe. Governments and companies are starting to regulate products and services to ensure digital accessibility as a mandatory requirement. A recent example is the European standard EN 301 [...] Read more.
Information and Communication Technologies (ICT) need to be accessible for every single person in the globe. Governments and companies are starting to regulate products and services to ensure digital accessibility as a mandatory requirement. A recent example is the European standard EN 301 549, where the functional accessibility requirements for ICT products and services are defined. Especially on the Web, these standards must be integrated throughout the development processes, where the selected architecture models play an essential role. Starting from a model that is based on the OAuth 2.0 protocol, and that allows the complete delegation of authorization (so that an as a service access control mechanism is provided), this paper propose an identity model for providing inclusive services and applications. The model takes advantage of the users’ profiles and their functional attributes to determine how to serve web interfaces to them in a specific service. Those attributes are entirely flexible, and can be defined linked to users’ functional capabilities, or even a particular skill. We have implemented the proposed model as an extension of an existing open source Identity Manager and tested it with a real use case deployment. We conclude that the proposed solution enables a new identity paradigm that allows service providers to design their interfaces satisfying the diversity requirements in terms of design and development. Full article
Open AccessArticle
Anomaly Detection of CAN Bus Messages Using a Deep Neural Network for Autonomous Vehicles
Appl. Sci. 2019, 9(15), 3174; https://doi.org/10.3390/app9153174 - 04 Aug 2019
Abstract
The in-vehicle controller area network (CAN) bus is one of the essential components for autonomous vehicles, and its safety will be one of the greatest challenges in the field of intelligent vehicles in the future. In this paper, we propose a novel system [...] Read more.
The in-vehicle controller area network (CAN) bus is one of the essential components for autonomous vehicles, and its safety will be one of the greatest challenges in the field of intelligent vehicles in the future. In this paper, we propose a novel system that uses a deep neural network (DNN) to detect anomalous CAN bus messages. We treat anomaly detection as a cross-domain modelling problem, in which three CAN bus data packets as a group are directly imported into the DNN architecture for parallel training with shared weights. After that, three data packets are represented as three independent feature vectors, which corresponds to three different types of data sequences, namely anchor, positive and negative. The proposed DNN architecture is an embedded triplet loss network that optimizes the distance between the anchor example and the positive example, makes it smaller than the distance between the anchor example and the negative example, and realizes the similarity calculation of samples, which were originally used in face detection. Compared to traditional anomaly detection methods, the proposed method to learn the parameters with shared-weight could improve detection efficiency and detection accuracy. The whole detection system is composed of the front-end and the back-end, which correspond to deep network and triplet loss network, respectively, and are trainable in an end-to-end fashion. Experimental results demonstrate that the proposed technology can make real-time responses to anomalies and attacks to the CAN bus, and significantly improve the detection ratio. To the best of our knowledge, the proposed method is the first used for anomaly detection in the in-vehicle CAN bus. Full article
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