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Processes
Special Issues
New Energy and Advanced Energy Saving Technology
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New Energy and Advanced Energy Saving Technology

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: closed (31 January 2023) | Viewed by 3008

Special Issue Editor

Dr. Christian Schneider

E-Mail Website
Guest Editor
Institute for Energy Efficiency in Production (EEP), University of Stuttgart, 70569 Stuttgart, Germany
Interests: energy efficiency; decision models; optimization

Special Issue Information

Dear Colleagues,

New energy and advanced energy-saving technology are one of the keys for the future of sustainable energy due to the ever-increasing importance of environmental issues (e.g., global climate change). The reduction of energy consumption through new technologies plays a key role in this context.

In order to achieve the savings targets that have been set, innovative technologies for all energy sources are necessary, ranging from electricity to heat. Approaches can focus on reducing energy consumption in existing systems or consist of innovative energy-efficient technologies.

This Special Issue invites all forms of contributions (communications, full papers, perspectives, and comments). All topics foucsing on energy-saving technologies are welcomed, ranging from data-driven approaches to material science. Both fundamental and applied research in new energy and advanced energy-saving technologies via experimental or computational methods are also welcome.

Dr. Christian Schneider
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 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. Processes 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 2400 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 (1 paper)

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Research

20 pages, 5225 KiB  
Article
Comparison of IoT Communication Protocols Using Anomaly Detection with Security Assessments of Smart Devices
by Akashdeep Bhardwaj, Keshav Kaushik, Salil Bharany, Mohamed F. Elnaggar, Mohamed I. Mossad and Salah Kamel
Processes 2022, 10(10), 1952; https://doi.org/10.3390/pr10101952 - 27 Sep 2022
Cited by 5 | Viewed by 2700
Abstract
The authors implemented an attack scenario that involved simulating attacks to compromise node and sensor data. This research proposes a framework with algorithms that generates automated malicious commands which conform to device protocol standards and bypass compromise detection. The authors performed attack-detection testing [...] Read more.
The authors implemented an attack scenario that involved simulating attacks to compromise node and sensor data. This research proposes a framework with algorithms that generates automated malicious commands which conform to device protocol standards and bypass compromise detection. The authors performed attack-detection testing with three different home setup simulations and referred to Accuracy of Detection, Ease of Precision, and Attack Recall, with the F1-Score as the parameter. The results obtained for anomaly detection of IoT logs and messages used K-Nearest Neighbor, Multilayer Perceptron, Logistic Regression, Random Forest, and linear Support Vector Classifier models. The attack results presented false-positive responses with and without the proposed framework and false-negative responses for different models. This research calculated Precision, Accuracy, F1-Score, and Recall as attack-detection performance models. Finally, the authors evaluated the performance of the proposed IoT communication protocol attack framework by evaluating a range of anomalies and compared them with the maliciously generated log messages. IoT Home #1 results in which the model involving an IP Camera and NAS device traffic displayed 97.7% Accuracy, 96.54% Precision, 97.29% Recall, and 96.88% F1-Score. This demonstrated that the model classified the Home #1 dataset consistently. Full article
(This article belongs to the Special Issue New Energy and Advanced Energy Saving Technology)
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