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Article
Computer Science, Theory & Methods
Prabhat Kumar et al.
Summary: This article presents a method for secure data transmission in IoT-enabled healthcare system using blockchain and deep learning. It ensures data integrity and secure transmission through a novel scalable blockchain architecture with Zero Knowledge Proof mechanism, and addresses storage cost and security issues by integrating off-chain storage and smart contracts. Experimental results demonstrate that the proposed method outperforms existing techniques in both non-blockchain and blockchain settings, achieving accuracy close to 99%.
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Muna Al-Hawawreh et al.
Summary: Internet of Medical Things (IoMT) devices and systems are often designed without adequate security, leaving them highly susceptible to cyber threats. This study proposes a privacy-aware framework that securely stores and fuses data from heterogeneous IoMT devices using differential privacy and deep learning, and efficiently detects cyber-attacks using quantum deep learning. Experimental results show that the proposed framework is highly effective in detecting cyber-attacks.
INFORMATION FUSION
(2023)
Article
Engineering, Chemical
Kedalu Poornachary Vijayakumar et al.
Article
Computer Science, Interdisciplinary Applications
Mohamed Abd Elaziz et al.
Summary: This paper proposes an efficient intrusion detection system for IoT-cloud based environments, using swarm intelligence algorithms and deep neural networks. Deep neural networks are used to obtain optimal features from IoT IDS data, and a feature selection technique based on the Capuchin Search Algorithm (CapSA) is proposed. The developed model, CNN-CapSA, is tested with four IoT-Cloud datasets and compared with other optimization algorithms, showing competitive performance.
ADVANCES IN ENGINEERING SOFTWARE
(2023)
Review
Computer Science, Information Systems
Barjinder Kaur et al.
Summary: The evolution of mobile technologies has introduced smarter and more connected objects into our day-to-day lives, known as the Internet of Things (IoT). However, the IoT also brings cybersecurity threats due to different communication standards, weak security defaults, and the difficulty of updating. To address these threats, developing a robust intrusion detection framework specifically for IoT is a promising approach.
INTERNET OF THINGS
(2023)
Article
Computer Science, Information Systems
Nazli Tekin et al.
Summary: Smart Home Systems (SHSs) have become popular with the development of Internet of Things (IoT) technologies. However, SHSs are vulnerable to attacks, leading to security and privacy concerns. Machine learning (ML)-based Intrusion Detection Systems (IDS) are proposed to address these concerns. Training ML models on-device can ensure data security and privacy, but it requires high energy consumption.
INTERNET OF THINGS
(2023)
Article
Computer Science, Artificial Intelligence
Robson V. Mendonca et al.
Summary: With the substantial industrial growth, the emergence of IIoT and various IoT fields have brought new challenges in terms of security issues, which require improved solutions for intelligent decision-making actions. A prediction model based on sparse evolutionary training (SET) is proposed in this paper to analyze and detect cybersecurity attacks in IIoT, achieving high accuracy and improving attack detection in Industry 4.0.
Article
Chemistry, Analytical
Muhammad Husnain et al.
Summary: In this paper, a MQTT parsing engine is designed and developed to serve as an initial layer in network-based IDS for extensive checking of IoT protocol vulnerabilities and improper usage. By rigorously validating packet fields, the proposed solution effectively detects and prevents the exploitation of vulnerabilities on IoT protocols.
Review
Computer Science, Information Systems
Yilin Yang et al.
Summary: The growth of the Internet of Things (IoT) has greatly contributed to the modernization of healthcare systems, allowing for various applications such as fitness tracking and sleep monitoring. This article surveys studies on smart health monitoring systems and the types of sensors used in the IoT. It analyzes these works based on their device-based and device-free techniques, as well as the signal processing and classification techniques used. The article discusses the creative application of these techniques to support professional and commercial health-monitoring IoT networks and identifies limitations and potential future research directions.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Nirmala Devi Kathamuthu et al.
Summary: The healthcare industry is being transformed by the Internet of Things (IoT), which enables connectivity among various stakeholders for real-time monitoring. In this study, a deep Q-learning-based neural network with privacy preservation method (DQ-NNPP) was developed to protect patient data transmission from external threats. Compared to other approaches, the proposed method achieved high accuracy and reduced communication overhead.
Article
Computer Science, Hardware & Architecture
Amiya Kumar Sahu et al.
Summary: The security of IoT continues to be a significant concern, with current research focusing on external attacks. However, internal devices or users within the network may pose a greater threat, highlighting the need for a security system that can continuously authenticate legitimate users.
COMPUTERS & ELECTRICAL ENGINEERING
(2022)
Article
Automation & Control Systems
Panagiotis Radoglou-Grammatikis et al.
Summary: The rise of the Internet of Medical Things brings both benefits and concerns to the healthcare ecosystem. This article focuses on the IEC 60 870-5-104 protocol and investigates its cyberattacks. It proposes an intrusion detection and prevention system (IDPS) that can automatically detect and mitigate these attacks. The IDPS utilizes machine learning and software defined networking technologies, achieving high accuracy and performance.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Nanoscience & Nanotechnology
K. Thilagam et al.
Summary: This study proposes an IoT-based deep learning privacy preservation and data analytics system to address security issues in healthcare systems. By collecting data from wearable devices and analyzing health-related information in the cloud, user privacy can be protected. The introduction of a secure access control module enables access control based on user attributes.
JOURNAL OF NANOMATERIALS
(2022)
Article
Chemistry, Analytical
Muhammad Aslam et al.
Summary: The development of smart network infrastructure for IoT faces the threat of DDoS attacks. The existing network security solutions are costly and unscalable for IoT. This paper proposes an Adaptive Machine Learning based SDN-enabled framework for detecting and mitigating DDoS attacks, which achieves higher accuracy and lower false alarm rate compared to existing solutions.
Article
Computer Science, Information Systems
Sudarshan Nandy et al.
Summary: The paper proposes an Empirical Intelligent Agent method based on Swarm-Neural network to identify attackers in the edge-centric Internet of Medical Things framework. Test results on the ToN-IoT dataset demonstrate that the proposed method achieves 99.5% accuracy in identifying attacks during data transmission.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2022)
Article
Automation & Control Systems
Mohit Kumar et al.
Summary: This article investigates how to enhance the security of the Internet of Medical Things using elliptic curve cryptography and Vigenere cipher, improving data security and privacy through algorithms for privacy preservation, neural networks, optimization methods, and blockchain technology.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Hardware & Architecture
Sohail Saif et al.
MICROPROCESSORS AND MICROSYSTEMS
(2022)
Article
Chemistry, Analytical
Mohammed Zubair et al.
Summary: The article introduces the use of artificial intelligence and deep learning to combat network attacks in smart health applications, and proposes an intrusion detection model and dataset based on deep learning. The research results show that the proposed intrusion detection model performs well in terms of F1 score and can effectively protect against attacks in smart health systems.
Review
Environmental Sciences
Lianxiao Meng et al.
Summary: This article focuses on the issue of spoofing in satellite navigation by analyzing the common interference types and classifying the spoofing modes based on signal generation, implementation stage, and deployment strategy. The research progress of GNSS anti-spoofing technology over the last decade is summarized, along with an analysis and comparison of current spoofing detection technologies. Considerations, prospective challenges, and development trends of GNSS spoofing and anti-spoofing technology are also discussed.
Article
Green & Sustainable Science & Technology
Amit Sundas et al.
Summary: Utilizing the Internet of Things and ubiquitous computing has made the healthcare system smarter. The Smart Healthcare System (SHS) monitors patients in real-time to prevent fatal illnesses, but it also faces security threats. This study introduces HealthGuard, a security architecture that uses machine learning to identify harmful actions taken by users, and shows promising results.
Article
Orieb AbuAlghanam et al.
Journal of Ambient Intelligence and Humanized Computing
(2022)
Article
Computer Science, Information Systems
Long Liu et al.
Summary: This research proposes a permissioned blockchain and deep reinforcement learning (DRL)-empowered Healthcare Internet of Things (H-IoT) system to address the security and limited energy capacity issues in the large-scale application of H-IoT. The proposed system can provide real-time security and energy-efficient healthcare services to control the propagation of the COVID-19 pandemic.
Review
Computer Science, Information Systems
R. Somasundaram et al.
Summary: The integration of computer science and electronics has led to the notable technology of the Internet of Things (IoT), with widespread applications in various fields including healthcare. However, the increasing security issues in IoT systems pose threats to patient health and safety. Addressing device-level security is crucial, while communication-level security requires more attention. An analysis of security issues in IoMTs helps to identify different risk factors for security attacks.
Article
Computer Science, Hardware & Architecture
A. S. Albahri et al.
Summary: Many studies have focused on smart telemedicine through IoT technology, exploring applications in network communications, artificial intelligence, IoT sensors, etc. This study filters and classifies 2121 papers, presenting a classification of IoT-based telemedicine architecture and revealing new research opportunities and challenges.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Mohiuddin Ahmed et al.
Summary: This paper presents the development of a new dataset, ECU-IoHT, to assist the healthcare security community in analyzing attack behavior and developing robust countermeasures. The study found that nearest neighbor-based algorithms outperformed clustering, statistical, and kernel-based anomaly detection algorithms in identifying cyberattacks.
Article
Computer Science, Hardware & Architecture
Wei Li et al.
Summary: The outbreak of chronic diseases like COVID-19 has highlighted the importance of urgent healthcare facilities worldwide, with smart wearables playing a vital role in modern healthcare solutions through IoT data collection. The application of big data analytics and machine learning techniques in IoT healthcare is growing, but there is a need for more research focusing on ML-based techniques in this sector.
MOBILE NETWORKS & APPLICATIONS
(2021)
Article
Chemistry, Analytical
Ankita Anand et al.
Summary: The role of 5G-IoT is essential in smart applications, especially in e-health. The proposed CNN-DMA deep learning model accurately detects malware attacks.
Article
Computer Science, Artificial Intelligence
Sahand Hariri et al.
Summary: The Extended Isolation Forest (EIF) proposes improvements to the Isolation Forest algorithm, addressing issues with assigning anomaly scores to data points. The paper explains the artifacts in anomaly score heat maps and suggests two different approaches for enhancement, with using hyperplanes with random slopes being the preferred method. The study shows that the algorithm's robustness is significantly improved using this method, without notable differences in convergence rate or computation time compared to the standard Isolation Forest.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2021)
Article
Chemistry, Analytical
Alberto Brunete et al.
Summary: This paper introduces a new architecture for a smart assistive environment that integrates IoT devices, service robots, and users, with a focus on supporting people with disabilities and bedbound patients. The interaction system allows users to control service robots and devices in five different ways: touch, eye, gesture, voice, and augmented reality control. The study presents user preferences for eye-based control and the use of mobile phones over augmented reality glasses in the context of the developed technology.
Article
Chemistry, Analytical
Faisal Hussain et al.
Summary: The rapid growth of IoT technology has revolutionized human life but also raised security concerns, especially in areas such as healthcare. Researchers need IoT-specific tools, methods, and datasets to address the security issues posed by IoT devices.
Review
Chemistry, Analytical
Muhammad Umair et al.
Summary: The COVID-19 pandemic has had a positive impact on the adoption of IoT in various industries, promoting the development of technology and innovation. Through research and expert interviews, the paper explores the influence of the pandemic on sectors such as healthcare, smart homes, and smart cities, and summarizes research directions and challenges that will accelerate IoT adoption.
Article
Computer Science, Information Systems
Md Abdur Rahman et al.
Summary: Medical IoT devices are being integrated into pandemic management systems like COVID-19, with researchers using deep learning algorithms to identify COVID-19 phenomena. However, these DL algorithms have security vulnerabilities to adversarial perturbations, making DL models vulnerable to attacks without defensive mechanisms.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Review
Computer Science, Information Systems
Mohammad Nuruzzaman Bhuiyan et al.
Summary: The Internet of Things (IoT) is a system that allows real-world things to interact and communicate with each other through networking technologies. This article reviews the advancements in IoT-based healthcare methods and technologies, discussing security, privacy, market opportunities, and more. It identifies research gaps and potential areas for sustainable development in IoT healthcare.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Review
Computer Science, Information Systems
Ritika Lohiya et al.
Summary: IoT is evolving towards the Internet of Everything, encompassing wireless networks, sensors, cloud servers, smart devices, and advanced technologies. Its applications span various sectors such as transportation, healthcare, and agriculture. Challenges in IoT research and commercial solutions developed in IoT application domains are highlighted in this article.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Yakub Kayode Saheed et al.
Summary: Advancements in ICT have changed the computing paradigm, with IoT providing new communication channels in the medical field but also posing security challenges.
Review
Computer Science, Information Systems
Rasheed Ahmad et al.
Summary: As IoT applications continue to expand, attacks on them are growing rapidly, with recent research trends emphasizing the development of models that integrate big data and machine learning technologies for better security.
INTERNET OF THINGS
(2021)
Review
Multidisciplinary Sciences
Amani Aldahiri et al.
Summary: Machine learning in combination with IoT is crucial in healthcare for intelligent decision-making, real-time patient monitoring, and disease prediction. Different ML algorithms may have varying impacts on prediction results, especially in clinical decision-making processes. Optimizing the choice of ML algorithms based on IoT datasets is essential for predicting critical healthcare data accurately.
Review
Computer Science, Information Systems
Taher M. Ghazal et al.
Summary: Smart city is a concept that aims to make cities more efficient, technologically advanced, greener and socially inclusive. The focus is on using digital technologies to address challenges faced by urban society, with particular potential in the healthcare sector.
Article
Computer Science, Information Systems
Fatima Alshehri et al.
Summary: Smart health care, a key aspect of connected living, is expected to generate billions of dollars in revenue. This field encompasses IoT, AI, and other cutting-edge technologies. Addressing research challenges and proposing future research directions are crucial for advancing smart health care.
Article
Computer Science, Information Systems
Ata Ullah et al.
Summary: The Internet of medical things (IoMT) has attracted researchers' attention due to its wide applicability in healthcare. Smart healthcare sensors and IoT enabled medical devices securely exchange sensitive healthcare data towards server nodes without human interaction, but face challenges in data communications, security, and privacy. This paper surveys different data collection and secure transmission schemes based on fog computing architectures, categorizes these schemes, and discusses open research challenges in the field.
Article
Management
Ding Yangke et al.
Summary: The paper reviews recent research and applications of smart logistics based on IoT, highlighting main technologies, impacts, challenges, and research needs in the field.
INTERNATIONAL JOURNAL OF LOGISTICS-RESEARCH AND APPLICATIONS
(2021)
Article
Chemistry, Analytical
Ankita Anand et al.
Summary: 5G-IoT plays an indispensable role in smart applications and is crucial in e-health applications. Intelligent schemes and architectures are required to overcome security threats against sensitive patient data in e-health applications. Deep learning techniques can detect security attacks, but this requires hybrid models for support.
Review
Computer Science, Information Systems
Hemantha Krishna Bharadwaj et al.
Summary: The Internet of Things is driving rapid automation in the healthcare sector, with a focus on data gathering, processing, and accurate predictions using machine learning algorithms. This paper serves as a compilation and review of state of the art applications of ML algorithms in Healthcare Internet of Things.
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Reneilson Santos et al.
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(2020)
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(2020)
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IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2020)
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Trevor Hastie et al.
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Statistics & Probability
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