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Sensors
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Building Trustworthy and Dependable Infrastructure in the Internet of Things
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Building Trustworthy and Dependable Infrastructure in the Internet of Things

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 12415

Special Issue Editors

Dr. Younghee Park

E-Mail Website
Guest Editor
Department of Computer Engineering, San Jose State University, San Jose, CA 95192, USA
Interests: network and system security; software-defined networks; network function virtualization; internet of things security; blockchain; AI security
Special Issues, Collections and Topics in MDPI journals
Dr. Hyoungshick Kim

E-Mail Website
Guest Editor
Department of Computer Science and Engineering, College of Computing, Sungkyunkwan University, Seoul 06351, Republic of Korea
Interests: usable security; blockchain; security vulnerability analysis; data-driven security
Special Issues, Collections and Topics in MDPI journals
Dr. Donghyun (David) Kim

E-Mail Website
Guest Editor
Department of Computer Science, Georgia State University, Atlanta, GA 30303, USA
Interests: data science; cybersecurity algorithm design and analysis; machine learning; networking
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The advancement of smart devices, such as smart sensors, smart healthcare systems, and wearable devices has great impacts on human life and industry. Millions of smart devices are connected and communicated to deliver a lot of data related to humans, devices, and communications, but they are at risk of various attacks. The security of the Internet of Things (IoT) is the most significant urgent task to build a trustworthy and dependable infrastructure for IoT. This Special Issue aims to present various security solutions using innovative emerging technologies including blockchain, artificial intelligence, machine learning, and software-defined networking. This Special Issue is addressed to all types of security issues in IoT, such as device security, privacy, side-channel attacks, communication vulnerability, identity management, access control, and data security. Topics of interest include but are not limited to:

  • AI and ML/DL techniques for securing IoT;
  • Cyber threats and incident analysis in IoT;
  • Blockchain for IoT security;
  • Intrusion and anomaly detection techniques for IoT;
  • Secure protocol designs and new theory for IoT;
  • Lightweight cryptographic solutions for IoT;
  • Access control and identity management for IoT;
  • Device security and malware for IoT.

Dr. Younghee Park
Dr. Hyoungshick Kim
Dr. Donghyun (David) Kim
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 submissions that pass pre-check are 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. Sensors 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 2600 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.

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Published Papers (2 papers)

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Research

23 pages, 1944 KiB  
Article
Analysis of Autoencoders for Network Intrusion Detection
by Youngrok Song, Sangwon Hyun and Yun-Gyung Cheong
Sensors 2021, 21(13), 4294; https://doi.org/10.3390/s21134294 - 23 Jun 2021
Cited by 78 | Viewed by 8356
Abstract
As network attacks are constantly and dramatically evolving, demonstrating new patterns, intelligent Network Intrusion Detection Systems (NIDS), using deep-learning techniques, have been actively studied to tackle these problems. Recently, various autoencoders have been used for NIDS in order to accurately and promptly detect [...] Read more.
As network attacks are constantly and dramatically evolving, demonstrating new patterns, intelligent Network Intrusion Detection Systems (NIDS), using deep-learning techniques, have been actively studied to tackle these problems. Recently, various autoencoders have been used for NIDS in order to accurately and promptly detect unknown types of attacks (i.e., zero-day attacks) and also alleviate the burden of the laborious labeling task. Although the autoencoders are effective in detecting unknown types of attacks, it takes tremendous time and effort to find the optimal model architecture and hyperparameter settings of the autoencoders that result in the best detection performance. This can be an obstacle that hinders practical applications of autoencoder-based NIDS. To address this challenge, we rigorously study autoencoders using the benchmark datasets, NSL-KDD, IoTID20, and N-BaIoT. We evaluate multiple combinations of different model structures and latent sizes, using a simple autoencoder model. The results indicate that the latent size of an autoencoder model can have a significant impact on the IDS performance. Full article
(This article belongs to the Special Issue Building Trustworthy and Dependable Infrastructure in the Internet of Things)
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23 pages, 1365 KiB  
Article
Secure Encapsulation Schemes Using Key Recovery System in IoMT Environments
by Taehoon Kim, Wonbin Kim, Daehee Seo and Imyeong Lee
Sensors 2021, 21(10), 3474; https://doi.org/10.3390/s21103474 - 17 May 2021
Cited by 5 | Viewed by 2628
Abstract
Recently, as Internet of Things systems have been introduced to facilitate diagnosis and treatment in healthcare and medical environments, there are many issues concerning threats to these systems’ security. For instance, if a key used for encryption is lost or corrupted, then ciphertexts [...] Read more.
Recently, as Internet of Things systems have been introduced to facilitate diagnosis and treatment in healthcare and medical environments, there are many issues concerning threats to these systems’ security. For instance, if a key used for encryption is lost or corrupted, then ciphertexts produced with this key cannot be decrypted any more. Hence, this paper presents two schemes for key recovery systems that can recover the lost or the corrupted keys of an Internet of Medical Things. In our proposal, when the key used for the ciphertext is needed, this key is obtained from a Key Recovery Field present in the cyphertext. Thus, the recovered key will allow decrypting the ciphertext. However, there are threats to this proposal, including the case of the Key Recovery Field being forged or altered by a malicious user and the possibility of collusion among participating entities (Medical Institution, Key Recovery Auditor, and Key Recovery Center) which can interpret the Key Recovery Field and abuse their authority to gain access to the data. To prevent these threats, two schemes are proposed. The first one enhances the security of a multi-agent key recovery system by providing the Key Recovery Field with efficient integrity and non-repudiation functions, and the second one provides a proxy re-encryption function resistant to collusion attacks against the key recovery system. Full article
(This article belongs to the Special Issue Building Trustworthy and Dependable Infrastructure in the Internet of Things)
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