Security of Data & IoT Infrastructures, Cyber Security, and Intelligent IoT Techniques

A special issue of Infrastructures (ISSN 2412-3811). This special issue belongs to the section "Smart Infrastructures".

Deadline for manuscript submissions: closed (31 August 2021) | Viewed by 8627

Special Issue Editors


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Guest Editor
Internet of Things and People (IoTaP) Center, Department of Computer Science, Malmö University, Nordenskiöldsgatan, Malmö, Sweden
Interests: Internet of Things (IoT) Security; cyber and information security; digital forensics-incident response; cyber-physical system protection; critical infrastructure protection; cloud computing security; computer systems; distributed system security; threat hunting and modeling and cyber-security risk assessment

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Guest Editor
Department of Computer Science, Werth College of Science, Technology and Mathematics, Fort Hays State University, Hays, KS 67601, USA
Interests: data mining; machine learning; pattern recognition; association rule mining; genetic algorithm; neural network; predictive analytics; big data; cloud computing; Internet of Things (IoT)

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Guest Editor
CiTIUS Research Center, University of Santiago de Compostela, Rúa de Jenaro de la Fuente Domínguez, 15782 Santiago de Compostela, Spain
Interests: big data; HPC; cloud computing; IoT; edge/fog analytics; Hadoop stack; data streaming; data security; data privacy; resource management

E-Mail Website
Guest Editor
IOTAP research center – Computer science department-Malmo University, Malmo, Sweden
Interests: big data; machine learning; interactive learning; IoT; cloud computing; data security; data privacy; federated learning; blockchain

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) paradigm has revolutionized how objects and devices sense, communicate, and interact across different environments and this has led to massive interconnectivity amongst devices. Mostly, at the center of this network of objects, is data that is exchanged, stored, and processed among connected devices. Driven by the fact that IoT is the major enabler of next-generation ubiquitous and pervasive computing, security and privacy have become key areas of concern. This Special Issue aims to uncover the latest significant knowledge that is based on practical investigations on the security of IoT Infrastructures, cyber-physical protection, and machine learning in IoT approaches that can be used to guarantee the safety of IoT infrastructures. As a result, this Special Issue welcomes relevant contributions from researchers, that offer pertinent solutions on open problems, existing, or future challenges in IoT infrastructures from academia and industry perspectives.

We would like to solicit papers in the following areas:

  • Security and privacy solutions in IoT ecosystems
  • Machine learning in IoT
  • Anomaly detection in IoT systems
  • Offensive security techniques in IoT Infrastructures
  • Critical infrastructure systems (CIS) protection approaches
  • Interactive and federated learning techniques in IoT environments
  • Edge and fog protection techniques
  • Security metrics for microservices in IoT ecosystems
  • Vulnerability and threat detection techniques
  • Incident detection and investigation techniques across IoT environments
  • Cloud computing security
  • Malware analysis and detection in IoT
  • Experiments, testbeds, and case studies in IoT infrastructure
  • Cyber-physical system (CPS) protection
  • IoT forensics
  • IoT infrastructure application areas
  • Big data security
  • AI & Security

Dr. Victor R. Kebande
Dr. Anas Hourani
Dr. Feras M. Awaysheh
Dr. Sadi A. M. Alawadi
Guest Editors

Manuscript Submission Information

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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. Infrastructures is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

  • Intelligent IoT and critical infrastructures
  • Cyber security and IoT forensics
  • Offensive security
  • Big data and machine learning
  • Threat analysis and detection
  • Adversarial detection strategies in IoT

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Published Papers (2 papers)

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Research

17 pages, 1910 KiB  
Article
Realising a Push Button Modality for Video-Based Forensics
by Bako Zawali, Richard A. Ikuesan, Victor R. Kebande, Steven Furnell and Arafat A-Dhaqm
Infrastructures 2021, 6(4), 54; https://doi.org/10.3390/infrastructures6040054 - 2 Apr 2021
Cited by 17 | Viewed by 3703
Abstract
Complexity and sophistication among multimedia-based tools have made it easy for perpetrators to conduct digital crimes such as counterfeiting, modification, and alteration without being detected. It may not be easy to verify the integrity of video content that, for example, has been manipulated [...] Read more.
Complexity and sophistication among multimedia-based tools have made it easy for perpetrators to conduct digital crimes such as counterfeiting, modification, and alteration without being detected. It may not be easy to verify the integrity of video content that, for example, has been manipulated digitally. To address this perennial investigative challenge, this paper proposes the integration of a forensically sound push button forensic modality (PBFM) model for the investigation of the MP4 video file format as a step towards automated video forensic investigation. An open-source multimedia forensic tool was developed based on the proposed PBFM model. A comprehensive evaluation of the efficiency of the tool against file alteration showed that the tool was capable of identifying falsified files, which satisfied the underlying assertion of the PBFM model. Furthermore, the outcome can be used as a complementary process for enhancing the evidence admissibility of MP4 video for forensic investigation. Full article
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19 pages, 4647 KiB  
Article
Face Validation of Database Forensic Investigation Metamodel
by Arafat Al-Dhaqm, Shukor Razak, Richard A. Ikuesan, Victor R. Kebande and Siti Hajar Othman
Infrastructures 2021, 6(2), 13; https://doi.org/10.3390/infrastructures6020013 - 20 Jan 2021
Cited by 30 | Viewed by 3805
Abstract
Using a face validity approach, this paper provides a validation of the Database Forensic Investigation Metamodel (DBFIM). The DBFIM was developed to solve interoperability, heterogeneity, complexity, and ambiguity in the database forensic investigation (DBFI) field, where several models were identified, collected, and reviewed [...] Read more.
Using a face validity approach, this paper provides a validation of the Database Forensic Investigation Metamodel (DBFIM). The DBFIM was developed to solve interoperability, heterogeneity, complexity, and ambiguity in the database forensic investigation (DBFI) field, where several models were identified, collected, and reviewed to develop DBFIM. However, the developed DBFIM lacked the face validity-based approach that could ensure DBFIM’s applicability in the DBFI field. The completeness, usefulness, and logic of the developed DBFIM needed to be validated by experts. Therefore, the objective of this paper is to perform the validation of the developed DBFIM using the qualitative face validity approach. The face validity method is a common way of validating metamodels through subject expert inquiry on the domain application of the metamodel to assess whether the metamodel is reasonable and compatible based on the outcomes. For this purpose, six experts were nominated and selected to validate the developed DBFIM. From the expert review, the developed DBFIM was found to be complete, coherent, logical, scalable, interoperable, and useful for the DBFI field. Full article
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