Review
Computer Science, Information Systems
Ali Ghubaish, Tara Salman, Maede Zolanvari, Devrim Unal, Abdulla Al-Ali, Raj Jain
Summary: The advancements in Internet of Things (IoT) technologies have transformed the healthcare industry through remote patient monitoring, enhancing patient care efficiency. Yet, the security of these systems remains a major challenge, requiring robust measures to safeguard data.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Artificial Intelligence
Ghulam Muhammad, Fatima Alshehri, Fakhri Karray, Abdulmotaleb El Saddik, Mansour Alsulaiman, Tiago H. Falk
Summary: Smart healthcare integrates technologies like wearables, IoMT, machine learning, and wireless communication to access health records and link resources. The fusion of multimodal medical signals is a key research focus in this field, with recent developments and challenges being explored in the survey of research works from 2014-2020.
INFORMATION FUSION
(2021)
Article
Computer Science, Hardware & Architecture
Yanyan Ji, Jinyong Chang, Qiaochuan Ren, Maozhi Xu, Rui Xue
Summary: The combination of Internet-of-Medical-Things technology and medical cloud storage has the potential to greatly enhance smart healthcare. However, there are challenges in ensuring privacy and authentication of medical data, as well as checking data integrity on the cloud. This paper proposes a secure and lightweight data management model, using encryption techniques and a certificateless signature scheme to address these issues.
Editorial Material
Automation & Control Systems
Syed Hassan Ahmed Shah, Deepika Koundal, Vyasa Sai, Shalli Rani
Summary: The relationship between computing and healthcare has a long history, but the adoption of telemedicine has been slow due to political resistance, lack of infrastructure development frameworks, and lack of resources. The Internet of Medical Things (IoMT) is expected to bring about significant advancements, particularly when combined with edge computing and 5G speed. Artificial intelligence and edge computing have played a crucial role in improving the network for reliable communication in smart healthcare systems.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Review
Green & Sustainable Science & Technology
Shadab Alam, Mohammed Shuaib, Sadaf Ahmad, Dushantha Nalin K. Jayakody, Ammar Muthanna, Salil Bharany, Ibrahim A. Elgendy
Summary: The combination of IoT and medical devices has transformed healthcare monitoring, and fog computing is a promising approach to handle resource limitations. Blockchain can address privacy and security concerns in fog computing.
Review
Chemistry, Multidisciplinary
Hamed Taherdoost
Summary: It is challenging to design a scalable blockchain for IoMT systems due to the involvement of IoT wearable medical equipment, healthcare facilities, patients, and insurance firms. This study comprehensively analyzes blockchain-based IoMT solutions developed in English from 2017 to 2022, aiming to standardize evaluation methods and keep up with the rapidly evolving blockchain space. It categorizes blockchain-enabled applications across various industries and highlights the gaps and restrictions posed by blockchain technology.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Hardware & Architecture
M. A. Jabbar, Shishir Kumar Shandilya, Ajit Kumar, Smita Shandilya
Summary: The sudden outbreak of COVID-19 has led to global lockdowns and showcased the need for a robust system using IoT technology for prevention and control of contagious diseases. IoT applications in healthcare, particularly the Cognitive Internet of Medical Things, offer promising solutions for monitoring, tracking, diagnosing, and controlling pandemics.
COMPUTERS & ELECTRICAL ENGINEERING
(2022)
Article
Computer Science, Information Systems
Jiangfeng Sun, Fazlullah Khan, Junxia Li, Mohammad Dahman Alshehri, Ryan Alturki, Mohammad Wedyan
Summary: This article presents a mutual authentication scheme for devices-to-server and vice versa in the operational Internet of Medical Things to ensure secure communication sessions among multiple mobile devices and servers. By introducing an offline phase for registration process, blocking potential intruder devices, and using encryption and decryption schemes, data reliability is ensured during communication sessions.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Review
Chemistry, Analytical
Mudassar Ali Khan, Ikram Ud Din, Tha'er Majali, Byung-Seo Kim
Summary: The Internet of medical things (IoMT) connects humans, devices, sensors, and systems to improve healthcare services. Although it brings efficient, accessible, and secure personalized health services, it also faces challenges. This survey explores authentication techniques proposed for IoT-enabled healthcare systems.
Article
Computer Science, Artificial Intelligence
Shams Forruque Ahmed, Md. Sakib Bin Alam, Shaila Afrin, Sabiha Jannat Rafa, Nazifa Rafa, Amir H. Gandomi
Summary: The Internet of Medical Things (IoMT) has opened up various opportunities for knowledge exchange in different industries. However, the adoption of IoMT faces challenges such as interoperability, data privacy, security, regulatory, and infrastructure costs. This paper focuses on the implications of data fusion in IoMT and addresses the security challenges and potential solutions.
INFORMATION FUSION
(2024)
Review
Chemistry, Multidisciplinary
Norah Alsaeed, Farrukh Nadeem
Summary: The Internet of Medical Things (IoMT) has transformed healthcare by connecting patients with providers remotely. Authentication is a crucial security measure in IoMT, but it is challenging due to diverse and resource-constrained devices. This systematic review examines 118 articles published between 2016 and 2021, identifying authentication schemes and trends. Most schemes use distributed architecture and public key infrastructure, with hybrid cryptography being popular. Future directions include support for end-to-end, cross-layer, and cross-domain authentication, and addressing open issues.
APPLIED SCIENCES-BASEL
(2022)
Article
Chemistry, Analytical
Pinky Bai, Sushil Kumar, Geetika Aggarwal, Mufti Mahmud, Omprakash Kaiwartya, Jaime Lloret
Summary: Identity management is crucial in smart healthcare systems, as traditional centralized systems suffer from security and privacy issues. Decentralized identity management is proposed as a robust solution, and a Self-Sovereign identity management system is introduced for the Internet of Medical Things (IoMT) environment. The proposed system gives users complete control over their data and is analyzed against established identity management guidelines for performance evaluation.
Article
Computer Science, Information Systems
K. Sowjanya, Mou Dasgupta, Sangram Ray
Summary: The paper discusses the design and security issues of anonymous authentication protocols in IoMT, proposing an improved lightweight Elliptic Curve Cryptography based solution that addresses security weaknesses in existing protocols. Security evaluations demonstrate the increased robustness of the proposed scheme.
JOURNAL OF INFORMATION SECURITY AND APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Mehedi Masud, Gurjot Singh Gaba, Salman Alqahtani, Ghulam Muhammad, B. B. Gupta, Pardeep Kumar, Ahmed Ghoneim
Summary: This article proposes a lightweight and physically secure mutual authentication and secret key establishment protocol for IoMT networks, which uses physical unclonable functions (PUFs) to verify the legitimacy of network devices before establishing session keys. The protocol provides necessary security properties such as authentication, confidentiality, integrity, and anonymity, demonstrating robustness against attacks through formal AVISPA and informal security analysis. It consumes fewer resources and is resilient against physical attacks, making it suitable for IoT-enabled medical network applications.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Theory & Methods
Izhar Ahmed Khan, Nour Moustafa, Imran Razzak, M. Tanveer, Dechang Pi, Yue Pan, Bakht Sher Ali
Summary: The Internet of Medical Things (IoMT) is replacing traditional healthcare systems, with less focus on security. Explainable AI (XAI) helps improve trust level and enables security experts to understand predictive decisions.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Computer Science, Artificial Intelligence
Amit Kumar Jaiswal, Prayag Tiwari, M. Shamim Hossain
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Heena Rathore, Amr Mohamed, Mohsen Guizani, Shailendra Rathore
Summary: This paper introduces a machine learning approach called NueroFATH for the physical assessment of athletes. It uses neural networks and fuzzy c-means techniques to predict the potential of athletes winning medals. The study also identifies important physical characteristics related to the assessment results.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Engineering, Civil
Moayad Aloqaily, Haya Elayan, Mohsen Guizani
Summary: The advancement of wireless connectivity in smart cities enhances connections between key elements, and the federated intelligent health monitoring systems in autonomous vehicles contribute to improving quality of life. This study proposes C-HealthIER, a cooperative health intelligent emergency response system that monitors passengers' health and conducts cooperative behavior to reduce emergency treatment time and distance by sharing information between vehicles and infrastructure.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Ghulam Muhammad, M. Shamim Hossain
Summary: This paper proposes light convolutional neural network (CNN) models for cognitive networking in an intelligent transportation system (ITS). The models include a 1D CNN for processing 1D temporal data and a deep tree CNN for processing image data from car camera sensors. By processing data independently on edge devices, the load and time of model execution are reduced. The proposed method achieves an accuracy of approximately 94-96% and an information density of 4.4 when tested on a publicly available facial emotion database.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Information Systems
Ikram Ud Din, Aniqa Bano, Kamran Ahmad Awan, Ahmad Almogren, Ayman Altameem, Mohsen Guizani
Summary: The increasing usage of the Internet has improved the quality of trust in the Internet of Things (IoT). Trust plays a crucial role in providing a secure environment for users to share private information and enable easy and trustworthy data exchange among IoT devices. Trust management is essential for secure data transmission in a large-scale IoT network, and a lightweight approach called LightTrust is proposed to address security issues in Industrial IoT nodes. LightTrust utilizes a centralized trust agent to generate and manage trust certificates, and direct observations and recommendations are used to develop trust between nodes. Comparative simulations demonstrate the effectiveness and resilience of the proposed approach.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Editorial Material
Computer Science, Theory & Methods
M. Shamim Hossain, Josu Bilbao, Diana P. P. Tobon, Abdulmotaleb El Saddik
Article
Engineering, Civil
Xiaoding Wang, Wenxin Liu, Hui Lin, Jia Hu, Kuljeet Kaur, M. Shamim Hossain
Summary: A hierarchical trajectory anomaly detection scheme is proposed for Intelligent Transportation Systems using machine learning and blockchain technologies, which can timely and effectively analyze and process trajectory big data, find hidden anomalies, and serve applications in urban planning, traffic management, safety control, etc.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Chemistry, Analytical
Esraa Hassan, Samir Elmougy, Mai R. Ibraheem, M. Shamim Hossain, Khalid AlMutib, Ahmed Ghoneim, Salman A. AlQahtani, Fatma M. Talaat
Summary: Retinal optical coherence tomography (OCT) imaging is a valuable tool for assessing the condition of the back part of the eye. In this paper, an enhanced OCT model based on modified ResNet (50) and random forest algorithms is proposed to classify retinal OCT. The experimentation results demonstrate high performance in sensitivity, specificity, and precision.
Article
Chemistry, Analytical
Tallat Jabeen, Ishrat Jabeen, Humaira Ashraf, N. Z. Jhanjhi, Abdulsalam Yassine, M. Shamim Hossain
Summary: The Internet of Things (IoT) employs wireless networks to deploy numerous wireless sensors for tracking system, physical, and environmental factors. This study proposes an intelligent healthcare system using nano sensors to collect real-time health status and transfer it to the doctor's server. A genetic-based encryption method is advocated for protecting data transmission over wireless channels, and an authentication procedure is proposed for user access to the data channel.
Article
Computer Science, Hardware & Architecture
Himanshi Babbar, Shalli Rani, Sahil Garg, Georges Kaddoum, Md. Jalil Piran, M. Shamim Hossain
Summary: This article proposes a secure multilayer SDN architecture that separates the paradigm into terrestrial, aerial, and ground domains and facilitates security solutions. The specifics of the architecture's development and implementation are explored, revealing some problems and unanswered questions. Descriptive results demonstrate that the proposed architecture will significantly improve the multilayer efficiency gains of configuration upgrading and decision-making.
IEEE CONSUMER ELECTRONICS MAGAZINE
(2023)
Article
Mathematics
Saad I. Nafisah, Ghulam Muhammad, M. Shamim Hossain, Salman A. AlQahtani
Summary: This study demonstrates the capabilities of computer-aided design (CAD) systems in identifying respiratory system disorders using chest X-ray (CXR) medical imaging. The proposed system based on explainable artificial intelligence is capable of detecting COVID-19 and visualizing the infected areas in CXR images, providing doctors with a second option for decision support.
Article
Computer Science, Theory & Methods
Liguo Dong, Zhenmou Liu, Kejia Zhang, Abdulsalam Yassine, M. Shamim Hossain
Summary: Federated Learning (FL) is a promising privacy computing framework for complex network systems. To incentivize data owners, it is important to fairly evaluate and compensate their contributions to the FL training process. The collaboration of FL and Shapley value, namely Federated Shapley Value (FedSV), provides an effective solution but faces challenges in computational overhead, privacy, and fairness in the FL setting.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2023)
Article
Engineering, Civil
Yazhou Zhang, Prayag Tiwari, Qian Zheng, Abdulmotaleb El Saddik, M. Shamim Hossain
Summary: Traffic events are a major cause of traffic accidents, and detecting these events poses a challenge in traffic management and intelligent transportation systems (ITSs). This paper proposes a multimodal coupled graph attention network (MCGAT) that extracts valuable information from various traffic data sources and represents it in a graphical structure. The proposed model outperforms state-of-the-art baselines in terms of F1 and accuracy, with significant improvements.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Abdulsalam Yassine, M. Shamim Hossain
Summary: The future Intelligent Transportation System (ITS) will heavily rely on the Internet of Things (IoT) and vehicle-to-vehicle (V2V) energy charging/discharging, enabled by low-power wide-area networks (LPWAN) or 5G wireless connection. A double-sided auction mechanism is proposed in this paper to maximize the benefits for EV owners by matching bids and asks for optimal social welfare.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Hardware & Architecture
Mhd Saria Allahham, Amr Mohamed, Aiman Erbad, Mohsen Guizani
Summary: Mobile edge learning (MEL) is a learning paradigm that enables distributed training of machine learning models over heterogeneous edge devices. This study proposes an incentive mechanism to motivate the participation of edge devices in the training process and evaluates its performance through numerical experiments.
IEEE CANADIAN JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING
(2023)
Editorial Material
Computer Science, Theory & Methods
Kiho Lim, Christian Esposito, Tian Wang, Chang Choi
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Editorial Material
Computer Science, Theory & Methods
Jesus Carretero, Dagmar Krefting
Summary: Computational methods play a crucial role in bioinformatics and biomedicine, especially in managing large-scale data and simulating complex models. This special issue focuses on security and performance aspects in infrastructure, optimization for popular applications, and the integration of machine learning and data processing platforms to improve the efficiency and accuracy of bioinformatics.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Renhao Lu, Weizhe Zhang, Qiong Li, Hui He, Xiaoxiong Zhong, Hongwei Yang, Desheng Wang, Zenglin Xu, Mamoun Alazab
Summary: Federated Learning allows collaborative training of AI models with local data, and our proposed FedAAM scheme improves convergence speed and training efficiency through an adaptive weight allocation strategy and asynchronous global update rules.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Qiangqiang Jiang, Xu Xin, Libo Yao, Bo Chen
Summary: This paper proposes a multi-objective energy-efficient task scheduling technique (METSM) for edge heterogeneous multiprocessor systems. A mathematical model is established for the task scheduling problem, and a problem-specific algorithm (IMO) is designed for optimizing task scheduling and resource allocation. Experimental results show that the proposed algorithm can achieve optimal Pareto fronts and significantly save time and power consumption.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Editorial Material
Computer Science, Theory & Methods
Weimin Li, Lu Liu, Kevin I. K. Wang, Qun Jin
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Mohammed Riyadh Abdmeziem, Amina Ahmed Nacer, Nawfel Moundji Deroues
Summary: Internet of Things (IoT) devices have become ubiquitous and brought the need for group communications. However, security in group communications is challenging due to the asynchronous nature of IoT devices. This paper introduces an innovative approach using blockchain technology and smart contracts to ensure secure and scalable group communications.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Robert Sajina, Nikola Tankovic, Ivo Ipsic
Summary: This paper presents and evaluates a novel approach that utilizes an encoder-only transformer model to enable collaboration between agents learning two distinct NLP tasks. The evaluation results demonstrate that collaboration among agents, even when working towards separate objectives, can result in mutual benefits.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Hebert Cabane, Kleinner Farias
Summary: Event-driven architecture has been widely adopted in the software industry for its benefits in software modularity and performance. However, there is a lack of empirical evidence to support its impact on performance. This study compares the performance of an event-driven application with a monolithic application and finds that the monolithic architecture consumes fewer computational resources and has better response times.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Haroon Wahab, Irfan Mehmood, Hassan Ugail, Javier Del Ser, Khan Muhammad
Summary: Wireless capsule endoscopy (WCE) is a revolutionary diagnostic method for small bowel pathology. However, the manual analysis of WCE videos is cumbersome and the privacy concerns of WCE data hinder the adoption of AI-based diagnoses. This study proposes a federated learning framework for collaborative learning from multiple data centers, demonstrating improved anomaly classification performance while preserving data privacy.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Maruf Monem, Md Tamjid Hossain, Md. Golam Rabiul Alam, Md. Shirajum Munir, Md. Mahbubur Rahman, Salman A. AlQahtani, Samah Almutlaq, Mohammad Mehedi Hassan
Summary: Bitcoin, the largest cryptocurrency, faces challenges in broader adaption due to long verification times and high transaction fees. To tackle these issues, researchers propose a learning framework that uses machine learning to predict the ideal block size in each block generation cycle. This model significantly improves the block size, transaction fees, and transaction approval rate of Bitcoin, addressing the long wait time and broader adaption problem.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Rafael Duque, Crescencio Bravo, Santos Bringas, Daniel Postigo
Summary: This paper introduces the importance of user interfaces for digital twins and presents a technique called ADD for modeling requirements of Human-DT interaction. A study is conducted to assess the feasibility and utility of ADD in designing user interfaces, using the virtualization of a natural space as a case study.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Xiulin Li, Li Pan, Wei Song, Shijun Liu, Xiangxu Meng
Summary: This article proposes a novel multiclass multi-pool analytical model for optimizing the quality of composite service applications deployed in the cloud. By considering embarrassingly parallel services and using differentiated parallel processing mechanisms, the model provides accurate prediction results and significantly reduces job response time.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Seongwan Park, Woojin Jeong, Yunyoung Lee, Bumho Son, Huisu Jang, Jaewook Lee
Summary: In this paper, a novel MEV detection model called ArbiNet is proposed, which offers a low-cost and accurate solution for MEV detection without requiring knowledge of smart contract code or ABIs.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Sacheendra Talluri, Nikolas Herbst, Cristina Abad, Tiziano De Matteis, Alexandru Iosup
Summary: Serverless computing is increasingly used in data-processing applications. This paper presents ExDe, a framework for systematically exploring the design space of scheduling architectures and mechanisms, to help system designers tackle complexity.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Chao Wang, Hui Xia, Shuo Xu, Hao Chi, Rui Zhang, Chunqiang Hu
Summary: This paper introduces a Federated Learning framework called FedBnR to address the issue of potential data heterogeneity in distributed entities. By breaking up the original task into multiple subtasks and reconstructing the representation using feature extractors, the framework improves the learning performance on heterogeneous datasets.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)