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Special Issue "Sensor Networks for Collaborative and Secure Internet of Things"

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

Deadline for manuscript submissions: 31 January 2018

Special Issue Editors

Guest Editor
Prof. Dr. Lei Shu

Guangdong University of Petrochemical Technology, China / University of Lincoln, UK
Website | E-Mail
Interests: wireless sensor networks; multimedia communication; middleware; security
Guest Editor
Prof. Dr. Mohsen Guizani

Department of Electrical and Computer Engineering, University of Idaho, USA
Website | E-Mail
Interests: wireless communications and mobile computing; computer networks; mobile cloud computing; security and smart grid
Guest Editor
Dr. Chunsheng Zhu

Department of Electrical and Computer Engineering, The University of British Columbia, Canada
Website | E-Mail
Interests: wireless sensor networks; cloud computing; Internet of Things; big data; social networks; security

Special Issue Information

Dear Colleagues,

Leveraging various information and communication technologies, our Internet is evolving into the Internet of Things (IoT) which aims to offer various comfortable and convenient services (e.g., smart climate control, smart street lighting, smart transportation, smart parking, and smart grid) to people. However, collaboration and security are identified as two critical issues that go under the radar of enthusiasts championing the IoT concept (i.e., connecting “Things” in the world). Specifically, research has shown that collaboration is the key to an open and accessible IoT. Investigation has found that security is the key to a trustable and robust IoT. In addition, collecting data from the “Things”, sensor networks act as the “eyes” and “ears” of IoT.

Therefore, toward a collaborative and secure IoT from the sensor networks perspective, this Special Issue solicits original technical papers with novel contributions on sensor networks taking into account the collaboration and security issues of IoT. Tutorial or survey papers are also welcome. In addition, selected high quality papers from Collaboratecom 2017 (http://collaboratecom.org/2017/show/home) will be invited for further consideration in this Special Issue for publication. Potential topics include, but are not limited to:

  • Communication in sensor networks for collaborative IoT
  • Communication in sensor networks for secure IoT
  • Computing in sensor networks for collaborative IoT
  • Computing in sensor networks for secure IoT
  • Middleware in sensor networks for collaborative IoT
  • Middleware in sensor networks for secure IoT
  • Cross-layer design in sensor networks for collaborative IoT
  • Cross-layer design in sensor networks for secure IoT
  • Testbed in sensor networks for collaborative IoT
  • Testbed in sensor networks for secure IoT
  • Novel application in sensor networks for collaborative IoT
  • Novel application in sensor networks for secure IoT                                  

Prof. Dr. Lei Shu
Prof. Dr. Mohsen Guizani
Dr. Chunsheng Zhu
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. Sensors 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 1800 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

  • Internet of Things
  • Collaboration
  • Security
  • Sensor network
  • Communication
  • Computing
  • Middleware

Published Papers (4 papers)

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Research

Open AccessArticle Secure Communications in CIoT Networks with a Wireless Energy Harvesting Untrusted Relay
Sensors 2017, 17(9), 2023; doi:10.3390/s17092023
Received: 8 August 2017 / Revised: 31 August 2017 / Accepted: 1 September 2017 / Published: 4 September 2017
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Abstract
The Internet of Things (IoT) represents a bright prospect that a variety of common appliances can connect to one another, as well as with the rest of the Internet, to vastly improve our lives. Unique communication and security challenges have been brought out
[...] Read more.
The Internet of Things (IoT) represents a bright prospect that a variety of common appliances can connect to one another, as well as with the rest of the Internet, to vastly improve our lives. Unique communication and security challenges have been brought out by the limited hardware, low-complexity, and severe energy constraints of IoT devices. In addition, a severe spectrum scarcity problem has also been stimulated by the use of a large number of IoT devices. In this paper, cognitive IoT (CIoT) is considered where an IoT network works as the secondary system using underlay spectrum sharing. A wireless energy harvesting (EH) node is used as a relay to improve the coverage of an IoT device. However, the relay could be a potential eavesdropper to intercept the IoT device’s messages. This paper considers the problem of secure communication between the IoT device (e.g., sensor) and a destination (e.g., controller) via the wireless EH untrusted relay. Since the destination can be equipped with adequate energy supply, secure schemes based on destination-aided jamming are proposed based on power splitting (PS) and time splitting (TS) policies, called intuitive secure schemes based on PS (Int-PS), precoded secure scheme based on PS (Pre-PS), intuitive secure scheme based on TS (Int-TS) and precoded secure scheme based on TS (Pre-TS), respectively. The secure performances of the proposed schemes are evaluated through the metric of probability of successfully secure transmission ( P S S T ), which represents the probability that the interference constraint of the primary user is satisfied and the secrecy rate is positive. P S S T is analyzed for the proposed secure schemes, and the closed form expressions of P S S T for Pre-PS and Pre-TS are derived and validated through simulation results. Numerical results show that the precoded secure schemes have better P S S T than the intuitive secure schemes under similar power consumption. When the secure schemes based on PS and TS polices have similar P S S T , the average transmit power consumption of the secure scheme based on TS is lower. The influences of power splitting and time slitting ratios are also discussed through simulations. Full article
(This article belongs to the Special Issue Sensor Networks for Collaborative and Secure Internet of Things)
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Open AccessArticle A Practical Evaluation of a High-Security Energy-Efficient Gateway for IoT Fog Computing Applications
Sensors 2017, 17(9), 1978; doi:10.3390/s17091978
Received: 28 July 2017 / Revised: 16 August 2017 / Accepted: 19 August 2017 / Published: 29 August 2017
PDF Full-text (16784 KB) | HTML Full-text | XML Full-text
Abstract
Fog computing extends cloud computing to the edge of a network enabling new Internet of Things (IoT) applications and services, which may involve critical data that require privacy and security. In an IoT fog computing system, three elements can be distinguished: IoT nodes
[...] Read more.
Fog computing extends cloud computing to the edge of a network enabling new Internet of Things (IoT) applications and services, which may involve critical data that require privacy and security. In an IoT fog computing system, three elements can be distinguished: IoT nodes that collect data, the cloud, and interconnected IoT gateways that exchange messages with the IoT nodes and with the cloud. This article focuses on securing IoT gateways, which are assumed to be constrained in terms of computational resources, but that are able to offload some processing from the cloud and to reduce the latency in the responses to the IoT nodes. However, it is usually taken for granted that IoT gateways have direct access to the electrical grid, which is not always the case: in mission-critical applications like natural disaster relief or environmental monitoring, it is common to deploy IoT nodes and gateways in large areas where electricity comes from solar or wind energy that charge the batteries that power every device. In this article, how to secure IoT gateway communications while minimizing power consumption is analyzed. The throughput and power consumption of Rivest–Shamir–Adleman (RSA) and Elliptic Curve Cryptography (ECC) are considered, since they are really popular, but have not been thoroughly analyzed when applied to IoT scenarios. Moreover, the most widespread Transport Layer Security (TLS) cipher suites use RSA as the main public key-exchange algorithm, but the key sizes needed are not practical for most IoT devices and cannot be scaled to high security levels. In contrast, ECC represents a much lighter and scalable alternative. Thus, RSA and ECC are compared for equivalent security levels, and power consumption and data throughput are measured using a testbed of IoT gateways. The measurements obtained indicate that, in the specific fog computing scenario proposed, ECC is clearly a much better alternative than RSA, obtaining energy consumption reductions of up to 50% and a data throughput that doubles RSA in most scenarios. These conclusions are then corroborated by a frame temporal analysis of Ethernet packets. In addition, current data compression algorithms are evaluated, concluding that, when dealing with the small payloads related to IoT applications, they do not pay off in terms of real data throughput and power consumption. Full article
(This article belongs to the Special Issue Sensor Networks for Collaborative and Secure Internet of Things)
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Open AccessArticle Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT
Sensors 2017, 17(9), 1967; doi:10.3390/s17091967
Received: 16 July 2017 / Revised: 22 August 2017 / Accepted: 22 August 2017 / Published: 26 August 2017
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Abstract
The purpose of a Network Intrusion Detection System is to detect intrusive, malicious activities or policy violations in a host or host’s network. In current networks, such systems are becoming more important as the number and variety of attacks increase along with the
[...] Read more.
The purpose of a Network Intrusion Detection System is to detect intrusive, malicious activities or policy violations in a host or host’s network. In current networks, such systems are becoming more important as the number and variety of attacks increase along with the volume and sensitiveness of the information exchanged. This is of particular interest to Internet of Things networks, where an intrusion detection system will be critical as its economic importance continues to grow, making it the focus of future intrusion attacks. In this work, we propose a new network intrusion detection method that is appropriate for an Internet of Things network. The proposed method is based on a conditional variational autoencoder with a specific architecture that integrates the intrusion labels inside the decoder layers. The proposed method is less complex than other unsupervised methods based on a variational autoencoder and it provides better classification results than other familiar classifiers. More important, the method can perform feature reconstruction, that is, it is able to recover missing features from incomplete training datasets. We demonstrate that the reconstruction accuracy is very high, even for categorical features with a high number of distinct values. This work is unique in the network intrusion detection field, presenting the first application of a conditional variational autoencoder and providing the first algorithm to perform feature recovery. Full article
(This article belongs to the Special Issue Sensor Networks for Collaborative and Secure Internet of Things)
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Open AccessArticle Lifetime Maximization via Hole Alleviation in IoT Enabling Heterogeneous Wireless Sensor Networks
Sensors 2017, 17(7), 1677; doi:10.3390/s17071677
Received: 20 June 2017 / Revised: 11 July 2017 / Accepted: 12 July 2017 / Published: 21 July 2017
PDF Full-text (503 KB) | HTML Full-text | XML Full-text
Abstract
In Internet of Things (IoT) enabled Wireless Sensor Networks (WSNs), there are two major factors which degrade the performance of the network. One is the void hole which occurs in a particular region due to unavailability of forwarder nodes. The other is the
[...] Read more.
In Internet of Things (IoT) enabled Wireless Sensor Networks (WSNs), there are two major factors which degrade the performance of the network. One is the void hole which occurs in a particular region due to unavailability of forwarder nodes. The other is the presence of energy hole which occurs due to imbalanced data traffic load on intermediate nodes. Therefore, an optimum transmission strategy is required to maximize the network lifespan via hole alleviation. In this regard, we propose a heterogeneous network solution that is capable to balance energy dissipation among network nodes. In addition, the divide and conquer approach is exploited to evenly distribute number of transmissions over various network areas. An efficient forwarder node selection is performed to alleviate coverage and energy holes. Linear optimization is performed to validate the effectiveness of our proposed work in term of energy minimization. Furthermore, simulations are conducted to show that our claims are well grounded. Results show the superiority of our work as compared to the baseline scheme in terms of energy consumption and network lifetime. Full article
(This article belongs to the Special Issue Sensor Networks for Collaborative and Secure Internet of Things)
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