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The Applications and Challenges of Cybersecurity in Science, Healthcare and...
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The Applications and Challenges of Cybersecurity in Science, Healthcare and Medicine

A special issue of Technologies (ISSN 2227-7080). This special issue belongs to the section "Information and Communication Technologies".

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 21588

Special Issue Editor

Dr. Mohammed Mahmoud

E-Mail Website
Guest Editor
Department of Computer Science, University of Jamestown, Jamestown, ND 58405, USA
Interests: data science; big data; machine learning; deep learning; artificial intelligence (AI); cybersecurity
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Healthcare is an attractive target for cybercrime as it contains extremely valuable data. Several issues currently complicate healthcare cybersecurity. To start, no healthcare organization exists to provide cybersecurity; they solely exist to provide healthcare. Additionally, there are increasing concerns relating to the security of healthcare data and devices. Increased connectivity to existing computer networks has exposed medical devices to new cybersecurity vulnerabilities.

Cybersecurity breaches include stealing health information, ransomware attacks on hospitals, and may include attacks on implanted medical devices. Such breaches can reduce patient trust, cripple health systems, and threaten human life.

Aligning cybersecurity and patient safety initiatives will not only help your organization to protect patient safety and privacy but will also ensure continuity of effective delivery of high-quality care by mitigating disruptions that have a negative impact on clinical outcomes. Rising cybersecurity threats to healthcare require policy makers to tackle fragmented governance, develop and implement security standards, and help organizations to improve their resilience. The goal behind this Special Issue is to discuss and present various tools, applications, and models in the context of cybersecurity, in addition to extensive and comprehensive concepts and techniques with regard to science, healthcare, and medicine. All related areas may also be considered.

Dr. Mohammed Mahmoud
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. Technologies 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 1600 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

  • cybersecurity
  • science
  • healthcare
  • medicine

Related Special Issue

Published Papers (6 papers)

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Research

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19 pages, 572 KiB  
Article
A Hypertuned Lightweight and Scalable LSTM Model for Hybrid Network Intrusion Detection
by Aysha Bibi, Gabriel Avelino Sampedro, Ahmad Almadhor, Abdul Rehman Javed and Tai-hoon Kim
Technologies 2023, 11(5), 121; https://doi.org/10.3390/technologies11050121 - 07 Sep 2023
Cited by 4 | Viewed by 1667
Abstract
Given the increasing frequency of network attacks, there is an urgent need for more effective network security measures. While traditional approaches such as firewalls and data encryption have been implemented, there is still room for improvement in their effectiveness. To effectively address this [...] Read more.
Given the increasing frequency of network attacks, there is an urgent need for more effective network security measures. While traditional approaches such as firewalls and data encryption have been implemented, there is still room for improvement in their effectiveness. To effectively address this concern, it is essential to integrate Artificial Intelligence (AI)-based solutions into historical methods. However, AI-driven approaches often encounter challenges, including lower detection rates and the complexity of feature engineering requirements. Finding solutions to overcome these hurdles is critical for enhancing the effectiveness of intrusion detection systems. This research paper introduces a deep learning-based approach for network intrusion detection to overcome these challenges. The proposed approach utilizes various classification algorithms, including the AutoEncoder (AE), Long-short-term-memory (LSTM), Multi-Layer Perceptron (MLP), Linear Support Vector Machine (L-SVM), Quantum Support Vector Machine (Q-SVM), Linear Discriminant Analysis (LDA), and Quadratic Discriminant Analysis (QDA). To validate the effectiveness of the proposed approach, three datasets, namely IOT23, CICIDS2017, and NSL KDD, are used for experimentation. The results demonstrate impressive accuracy, particularly with the LSTM algorithm, achieving a 97.7% accuracy rate on the NSL KDD dataset, 99% accuracy rate on the CICIDS2017 dataset, and 98.7% accuracy on the IOT23 dataset. These findings highlight the potential of deep learning algorithms in enhancing network intrusion detection. By providing network administrators with robust security measures for accurate and timely intrusion detection, the proposed approach contributes to network safety and helps mitigate the impact of network attacks. Full article
(This article belongs to the Special Issue The Applications and Challenges of Cybersecurity in Science, Healthcare and Medicine)
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17 pages, 3624 KiB  
Article
Modernizing the Legacy Healthcare System to Decentralize Platform Using Blockchain Technology
by Abdulaziz Aljaloud and Abdul Razzaq
Technologies 2023, 11(4), 84; https://doi.org/10.3390/technologies11040084 - 29 Jun 2023
Cited by 1 | Viewed by 1931
Abstract
The use of blockchain technology is expanding in various industries, including finance, supply chain management, food, energy, IoT, and healthcare. The article aims to address the challenges of complex medical procedures, large-scale medical data management, and cost optimization in the healthcare industry. By [...] Read more.
The use of blockchain technology is expanding in various industries, including finance, supply chain management, food, energy, IoT, and healthcare. The article aims to address the challenges of complex medical procedures, large-scale medical data management, and cost optimization in the healthcare industry. By employing blockchain technology, the article aims to enhance data security and privacy while ensuring the integrity and efficiency of the healthcare system. This article focuses on the application of blockchain technology in the healthcare system by reviewing the existing literature and proposing multiple workflows for better data management. These workflows were implemented using the Ethereum blockchain platform and involve complex medical procedures such as surgery and clinical trials, as well as managing a large amount of medical data. The feasibility of the proposed system is analyzed in terms of associated costs, and a model-driven engineering approach is used to recover the architecture of traditional healthcare systems. The aim is to provide stakeholders in the healthcare system with better healthcare services and cost optimization. The solution being proposed automates interactions between different parties involved. Smart contracts were created using Solidity language, and their functions were tested using the Remix IDE. This paper illustrates that our smart contract code was designed to avoid common security vulnerabilities and attacks. To test the framework, a prototype of the smart contract was deployed on an Ethereum TESTNET blockchain in a Windows environment. This study found that the proposed approach is both practical and efficient. Full article
(This article belongs to the Special Issue The Applications and Challenges of Cybersecurity in Science, Healthcare and Medicine)
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15 pages, 3285 KiB  
Article
NikshayChain: A Blockchain-Based Proposal for Tuberculosis Data Management in India
by Madhuri Hiwale, Vijayakumar Varadarajan, Rahee Walambe and Ketan Kotecha
Technologies 2023, 11(1), 5; https://doi.org/10.3390/technologies11010005 - 26 Dec 2022
Cited by 3 | Viewed by 2976
Abstract
A recent development in the Internet of Things (IoT) has accelerated the application of IoT-based solutions in healthcare. Next-Gen networks and IoT, supported by the development of technologies such as Artificial Intelligence (AI) and blockchain, have propelled the growth of e-health applications. However, [...] Read more.
A recent development in the Internet of Things (IoT) has accelerated the application of IoT-based solutions in healthcare. Next-Gen networks and IoT, supported by the development of technologies such as Artificial Intelligence (AI) and blockchain, have propelled the growth of e-health applications. However, there are some unique challenges in the widespread acceptance of IoT in healthcare. Safe storage, transfer, authorized access control, and the privacy and security aspects of patient data management are crucial barriers to the widespread adoption of IoT in healthcare. This makes it necessary to identify current issues in the various health data management systems to develop novel healthcare solutions. As a case study, this work considers a scheme launched by the Government of India for tuberculosis care called Nikshay Poshan Yojana (NPY). It is a web-based Direct Benefit Transfer scheme to provide a nutritional incentive of INR 500/- per month to all tuberculosis patients. The main objective of this work is to identify the current implementation challenges of the NPY scheme from patient and healthcare stakeholder perspectives and proposes a blockchain-based architecture called NikshayChain for sharing patient medical reports and bank details among several healthcare stakeholders within or across Indian cities. The proposed architecture accelerates healthcare stakeholder productivity by reducing workload and overall costs while ensuring effective data management. This architecture can significantly improve medical care, incentive transfer, and data verification, propelling the use of e-health applications. Full article
(This article belongs to the Special Issue The Applications and Challenges of Cybersecurity in Science, Healthcare and Medicine)
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18 pages, 3213 KiB  
Article
Efficiently Mitigating Face-Swap-Attacks: Compressed-PRNU Verification with Sub-Zones
by Ali Hassani, Hafiz Malik and Jon Diedrich
Technologies 2022, 10(2), 46; https://doi.org/10.3390/technologies10020046 - 27 Mar 2022
Cited by 2 | Viewed by 2909
Abstract
Face-swap-attacks (FSAs) are a new threat to face recognition systems. FSAs are essentially imperceptible replay-attacks using an injection device and generative networks. By placing the device between the camera and computer device, attackers can present any face as desired. This is particularly potent [...] Read more.
Face-swap-attacks (FSAs) are a new threat to face recognition systems. FSAs are essentially imperceptible replay-attacks using an injection device and generative networks. By placing the device between the camera and computer device, attackers can present any face as desired. This is particularly potent as it also maintains liveliness features, as it is a sophisticated alternation of a real person, and as it can go undetected by traditional anti-spoofing methods. To address FSAs, this research proposes a noise-verification framework. Even the best generative networks today leave alteration traces in the photo-response noise profile; these are detected by doing a comparison of challenge images against the camera enrollment. This research also introduces compression and sub-zone analysis for efficiency. Benchmarking with open-source tampering-detection algorithms shows the proposed compressed-PRNU verification robustly verifies facial-image authenticity while being significantly faster. This demonstrates a novel efficiency for mitigating face-swap-attacks, including denial-of-service attacks. Full article
(This article belongs to the Special Issue The Applications and Challenges of Cybersecurity in Science, Healthcare and Medicine)
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Review

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26 pages, 2231 KiB  
Review
A Comprehensive Survey of Cybersecurity Threats, Attacks, and Effective Countermeasures in Industrial Internet of Things
by Abdullah M. Alnajim, Shabana Habib, Muhammad Islam, Su Myat Thwin and Faisal Alotaibi
Technologies 2023, 11(6), 161; https://doi.org/10.3390/technologies11060161 - 13 Nov 2023
Cited by 2 | Viewed by 4100
Abstract
The Industrial Internet of Things (IIoT) ecosystem faces increased risks and vulnerabilities due to adopting Industry 4.0 standards. Integrating data from various places and converging several systems have heightened the need for robust security measures beyond fundamental connection encryption. However, it is difficult [...] Read more.
The Industrial Internet of Things (IIoT) ecosystem faces increased risks and vulnerabilities due to adopting Industry 4.0 standards. Integrating data from various places and converging several systems have heightened the need for robust security measures beyond fundamental connection encryption. However, it is difficult to provide adequate security due to the IIoT ecosystem’s distributed hardware and software. The most effective countermeasures must be suggested together with the crucial vulnerabilities, linked threats, and hazards in order to protect industrial equipment and ensure the secure functioning of IIoT systems. This paper presents a thorough analysis of events that target IIoT systems to alleviate such concerns. It also offers a comprehensive analysis of the responses that have been advanced in the most recent research. This article examines several kinds of attacks and the possible consequences to understand the security landscape in the IIoT area. Additionally, we aim to encourage the development of effective defenses that will lessen the hazards detected and secure the privacy, accessibility, and reliability of IIoT systems. It is important to note that we examine the issues and solutions related to IIoT security using the most recent findings from research and the literature on this subject. This study organizes and evaluates recent research to provide significant insight into the present security situation in IIoT systems. Ultimately, we provide outlines for future research and projects in this field. Full article
(This article belongs to the Special Issue The Applications and Challenges of Cybersecurity in Science, Healthcare and Medicine)
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50 pages, 3168 KiB  
Review
Smartphone Security and Privacy: A Survey on APTs, Sensor-Based Attacks, Side-Channel Attacks, Google Play Attacks, and Defenses
by Zia Muhammad, Zahid Anwar, Abdul Rehman Javed, Bilal Saleem, Sidra Abbas and Thippa Reddy Gadekallu
Technologies 2023, 11(3), 76; https://doi.org/10.3390/technologies11030076 - 12 Jun 2023
Cited by 3 | Viewed by 5562
Abstract
There is an exponential rise in the use of smartphones in government and private institutions due to business dependencies such as communication, virtual meetings, and access to global information. These smartphones are an attractive target for cybercriminals and are one of the leading [...] Read more.
There is an exponential rise in the use of smartphones in government and private institutions due to business dependencies such as communication, virtual meetings, and access to global information. These smartphones are an attractive target for cybercriminals and are one of the leading causes of cyber espionage and sabotage. A large number of sophisticated malware attacks as well as advanced persistent threats (APTs) have been launched on smartphone users. These attacks are becoming significantly more complex, sophisticated, persistent, and undetected for extended periods. Traditionally, devices are targeted by exploiting a vulnerability in the operating system (OS) or device sensors. Nevertheless, there is a rise in APTs, side-channel attacks, sensor-based attacks, and attacks launched through the Google Play Store. Previous research contributions have lacked contemporary threats, and some have proven ineffective against the latest variants of the mobile operating system. In this paper, we conducted an extensive survey of papers over the last 15 years (2009–2023), covering vulnerabilities, contemporary threats, and corresponding defenses. The research highlights APTs, classifies malware variants, defines how sensors are exploited, visualizes multiple ways that side-channel attacks are launched, and provides a comprehensive list of malware families that spread through the Google Play Store. In addition, the research provides details on threat defense solutions, such as malware detection tools and techniques presented in the last decade. Finally, it highlights open issues and identifies the research gap that needs to be addressed to meet the challenges of next-generation smartphones. Full article
(This article belongs to the Special Issue The Applications and Challenges of Cybersecurity in Science, Healthcare and Medicine)
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