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Advances in Secure Massive MIMO Systems
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Advances in Secure Massive MIMO Systems

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

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 17563

Special Issue Editors

Dr. Suleman Khan

E-Mail
Guest Editor
Department of Computer & Information Sciences, Northumbria University, Newcastle NE1 8QH, UK
Interests: software-defined networks; MIMO systems; IoT; edge computing; network security
Dr. Shahid Mumtaz

grade E-Mail Website
Guest Editor
Quantum Communication Instituto de Telecomunicaces, University Campus of Santiago, P-3810-193 Aveiro, Portugal
Interests: 5G-NR; quantum communication; machine learning; satellite communication
Special Issues, Collections and Topics in MDPI journals
Dr. Bin Jiang

E-Mail Website
Guest Editor
College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China
Interests: cyber-physical systems; privacy proctection; Internet of Things; industrial multimedia quality control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Recently, Massive multiple-input multiple-output (MIMO) systems have become a very promising technology for the next generation of wireless communication systems. Massive MIMO will not only be fulfilling the demand of the user’s multimedia services (high data rates) but will cope with the QoS. However, Massive MIMO techniques need time to mature in the next fews years to support future communication networks without any communication setbacks. Security is also considering key challenges for the Massive MIMO, especially when it is used in different areas, including smarty city, V2V communication, 5G, edge computing, and various others. In traditional networks, secure communication relies on cryptographic methods implemented at the network and application layers. These cryptographic methods require a reasonable computational time to decipher the message. To overcome this problem, a physical layer security mechanism is used in wireless communication to avoid encryption keys. Massive MIMO is equipped with thousands of antennas that are attached to the base station. This Special Issue focuses on how to protect these antennas, other physical devices, and communication from being hacked and exploited by the attackers—as Massive MIMO relies on secrecy. It is recommended to contribute work exploring novel techniques, models, frameworks, and architecture to aid secure Massive MIMO communication.

Dr. Suleman Khan
Dr. Shahid Mumtaz
Dr. Bin Jiang
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.

Keywords

  • Network security in Massive MIMO
  • QoS in Massive MIMO
  • Secure communication in Massive MIMO
  • Network forensic in Massive MIMO
  • The detection mechanism of attacks in Massive MIMO
  • Mitigation approaches for secure Massive MIMO
  • Smart cities using Massive MIMO
  • The role of Massive MIMO in autonomous vehicles
  • New technologies used in Massive MIMO.

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Published Papers (3 papers)

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Research

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21 pages, 3364 KiB  
Article
Prioritising Organisational Factors Impacting Cloud ERP Adoption and the Critical Issues Related to Security, Usability, and Vendors: A Systematic Literature Review
by Sayeed Salih, Mosab Hamdan, Abdelzahir Abdelmaboud, Ahmed Abdelaziz, Samah Abdelsalam, Maha M. Althobaiti, Omar Cheikhrouhou, Habib Hamam and Faiz Alotaibi
Sensors 2021, 21(24), 8391; https://doi.org/10.3390/s21248391 - 15 Dec 2021
Cited by 14 | Viewed by 6809
Abstract
Cloud ERP is a type of enterprise resource planning (ERP) system that runs on the vendor’s cloud platform instead of an on-premises network, enabling companies to connect through the Internet. The goal of this study was to rank and prioritise the factors driving [...] Read more.
Cloud ERP is a type of enterprise resource planning (ERP) system that runs on the vendor’s cloud platform instead of an on-premises network, enabling companies to connect through the Internet. The goal of this study was to rank and prioritise the factors driving cloud ERP adoption by organisations and to identify the critical issues in terms of security, usability, and vendors that impact adoption of cloud ERP systems. The assessment of critical success factors (CSFs) in on-premises ERP adoption and implementation has been well documented; however, no previous research has been carried out on CSFs in cloud ERP adoption. Therefore, the contribution of this research is to provide research and practice with the identification and analysis of 16 CSFs through a systematic literature review, where 73 publications on cloud ERP adoption were assessed from a range of different conferences and journals, using inclusion and exclusion criteria. Drawing from the literature, we found security, usability, and vendors were the top three most widely cited critical issues for the adoption of cloud-based ERP; hence, the second contribution of this study was an integrative model constructed with 12 drivers based on the security, usability, and vendor characteristics that may have greater influence as the top critical issues in the adoption of cloud ERP systems. We also identified critical gaps in current research, such as the inconclusiveness of findings related to security critical issues, usability critical issues, and vendor critical issues, by highlighting the most important drivers influencing those issues in cloud ERP adoption and the lack of discussion on the nature of the criticality of those CSFs. This research will aid in the development of new strategies or the revision of existing strategies and polices aimed at effectively integrating cloud ERP into cloud computing infrastructure. It will also allow cloud ERP suppliers to determine organisations’ and business owners’ expectations and implement appropriate tactics. A better understanding of the CSFs will narrow the field of failure and assist practitioners and managers in increasing their chances of success. Full article
(This article belongs to the Special Issue Advances in Secure Massive MIMO Systems)
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19 pages, 2563 KiB  
Article
SISME, Estuarine Monitoring System Based on IOT and Machine Learning for the Detection of Salt Wedge in Aquifers: Case Study of the Magdalena River Estuary
by Paola Patricia Ariza-Colpas, Cristian Eduardo Ayala-Mantilla, Qaisar Shaheen, Marlon Alberto Piñeres-Melo, Diego Andrés Villate-Daza, Roberto Cesar Morales-Ortega, Emiro De-la-Hoz-Franco, Hernando Sanchez-Moreno, Butt Shariq Aziz and Mehtab Afzal
Sensors 2021, 21(7), 2374; https://doi.org/10.3390/s21072374 - 29 Mar 2021
Cited by 7 | Viewed by 2802
Abstract
This article contains methods, results, and analysis agreed for the development of an application based on the internet of things and making use of machine learning techniques that serves as a support for the identification of the saline wedge in the Magdalena River [...] Read more.
This article contains methods, results, and analysis agreed for the development of an application based on the internet of things and making use of machine learning techniques that serves as a support for the identification of the saline wedge in the Magdalena River estuary, Colombia. As a result of this investigation, the process of identifying the most suitable telecommunications architecture to be installed in the estuary is shown, as well as the characteristics of the software developed called SISME (Estuary Monitoring System), and the results obtained after the implementation of prediction techniques based on time series. This implementation supports the maritime security of the port of Barranquilla since it can support decision-making related to the estuary. This research is the result of the project “Implementation of a Wireless System of Temperature, Conductivity and Pressure Sensors to support the identification of the saline wedge and its impact on the maritime safety of the Magdalena River estuary”. Full article
(This article belongs to the Special Issue Advances in Secure Massive MIMO Systems)
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Review

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15 pages, 1539 KiB  
Review
Cyber-Attack Prediction Based on Network Intrusion Detection Systems for Alert Correlation Techniques: A Survey
by Hashim Albasheer, Maheyzah Md Siraj, Azath Mubarakali, Omer Elsier Tayfour, Sayeed Salih, Mosab Hamdan, Suleman Khan, Anazida Zainal and Sameer Kamarudeen
Sensors 2022, 22(4), 1494; https://doi.org/10.3390/s22041494 - 15 Feb 2022
Cited by 36 | Viewed by 6950
Abstract
Network Intrusion Detection Systems (NIDS) are designed to safeguard the security needs of enterprise networks against cyber-attacks. However, NIDS networks suffer from several limitations, such as generating a high volume of low-quality alerts. Moreover, 99% of the alerts produced by NIDSs are false [...] Read more.
Network Intrusion Detection Systems (NIDS) are designed to safeguard the security needs of enterprise networks against cyber-attacks. However, NIDS networks suffer from several limitations, such as generating a high volume of low-quality alerts. Moreover, 99% of the alerts produced by NIDSs are false positives. As well, the prediction of future actions of an attacker is one of the most important goals here. The study has reviewed the state-of-the-art cyber-attack prediction based on NIDS Intrusion Alert, its models, and limitations. The taxonomy of intrusion alert correlation (AC) is introduced, which includes similarity-based, statistical-based, knowledge-based, and hybrid-based approaches. Moreover, the classification of alert correlation components was also introduced. Alert Correlation Datasets and future research directions are highlighted. The AC receives raw alerts to identify the association between different alerts, linking each alert to its related contextual information and predicting a forthcoming alert/attack. It provides a timely, concise, and high-level view of the network security situation. This review can serve as a benchmark for researchers and industries for Network Intrusion Detection Systems’ future progress and development. Full article
(This article belongs to the Special Issue Advances in Secure Massive MIMO Systems)
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