Special Issue "Security and Privacy for IoT and Multimedia Services"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 30 December 2020.

Special Issue Editors

Prof. Dr. Sang-Soo Yeo
Guest Editor
Division of Convergence Computer & Media, Mokwon University, Daejeon 35349, Korea
Interests: security; privacy; multimedia service; ubiquitous computing; embedded system; bioinformatics
Assoc. Prof. Dr. Damien Sauveron
Guest Editor
Faculty of Sciences and Techniques, XLIM (UMR CNRS 7252 / University of Limoges), 123, avenue Albert Thomas, 87060 Limoges Cedex, France
Interests: sensors network applications and security; smart home applications and security; IoT security; smart card applications and security; security of Java Card technology; RFID/NFC applications and security; mobile networks applications and security; vehicular network
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Special Issue Information

Dear Colleagues,  

In recent years, the rapid increase in the number of users connected to the Internet and the increase in the number of Internet-connected entities, such as DCE, DTE, smart appliance, and various “things”, have contributed to the rapid improvement in the style and quality of services over the Internet. Conversely, various service demands of users and quality of service demands are expanding the IoT world.  

These days, IoT services are changing the way we live. The stage whereby IoT products and services were introduced by some early adopters at home or in the office are now over. Now IPTV companies, ISPs, and mobile carriers with a large number of subscribers have launched various IoT products and provide a variety of user services, including AI-enabled multimedia services. Within a few years, most of OECD countries may enter the stage where IoT services have become mandatory and universally available to their people.  

The main aim of this Special Issue is to seek papers taking an academic perspective on security for IoT and its multimedia services. Security vulnerabilities and threats may be obstacles to the popularization and universalization of these technologically advanced IoT and multimedia services. We hope that your submitted articles will raise and respond to new security issues, or represent ongoing research to enhance the effectiveness and efficiency of existing security issues in IoT environments. We also welcome academic manuscripts covering security and privacy policies related to IoT and multimedia services.  

The topics of interest include, but are not limited to:       

  • Security architectures and platforms for IoT and multimedia services; 
  • Cryptographic protocols and cipher for the security in IoT and multimedia services;      
  • Malicious transactions detection in IoT and multimedia services;      
  • Redundancy and virtualization for IoT and multimedia services;      
  • Security and privacy for AI-enabled in-vehicle IoT services;      
  • Security and privacy Issues in smart homes;      
  • Security and privacy Issues in smart buildings;     
  • Security and privacy Issues in smart meters and microgrid services;      
  • IoT device and service issues in EU-GDPR;      
  • IoT device and service issues in APEC-CBPR;      
  • IoT service-related security issues between countries and/or international bodies.

Prof. Dr. Sang-Soo Yeo
Assoc. Prof. Dr. Damien Sauveron
Guest Editors

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. Electronics is an international peer-reviewed open access monthly 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 1400 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.


  • Security
  • Privacy
  • IoT
  • Multimedia service
  • Smart home
  • Smart buildings
  • Smart meters
  • In-vehicle IoT
  • GDPR
  • CBPR

Published Papers (1 paper)

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Open AccessFeature PaperArticle
Platform-Independent Malware Analysis Applicable to Windows and Linux Environments
Electronics 2020, 9(5), 793; https://doi.org/10.3390/electronics9050793 - 12 May 2020
Most cyberattacks use malicious codes, and according to AV-TEST, more than 1 billion malicious codes are expected to emerge in 2020. Although such malicious codes have been widely seen around the PC environment, they have been on the rise recently, focusing on IoT [...] Read more.
Most cyberattacks use malicious codes, and according to AV-TEST, more than 1 billion malicious codes are expected to emerge in 2020. Although such malicious codes have been widely seen around the PC environment, they have been on the rise recently, focusing on IoT devices such as smartphones, refrigerators, irons, and various sensors. As is known, Linux/embedded environments support various architectures, so it is difficult to identify the architecture in which malware operates when analyzing malware. This paper proposes an AI-based malware analysis technology that is not affected by the operating system or architecture platform. The proposed technology works intuitively. It uses platform-independent binary data rather than features based on the structured format of the executable files. We analyzed the strings from binary data to classify malware. The experimental results achieved 94% accuracy on Windows and Linux datasets. Based on this, we expect the proposed technology to work effectively on other platforms and improve through continuous operation/verification. Full article
(This article belongs to the Special Issue Security and Privacy for IoT and Multimedia Services)
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