Article
Computer Science, Hardware & Architecture
J. Andrew, Deva Priya Isravel, K. Martin Sagayam, Bharat Bhushan, Yuichi Sei, Jennifer Eunice
Summary: Blockchain has gained popularity due to its data integrity and wide range of applications. It has provided the foundation for cryptocurrencies like Ripple, Bitcoin, Ethereum, etc. Blockchain offers a decentralized and trustworthy platform for various applications such as finance, commerce, IoT, reputation systems, and healthcare. However, there are still challenges in terms of scalability, resilience, security, and privacy that need to be addressed.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
Rajani Singh, Ashutosh Dhar Dwivedi, Raghava Rao Mukkamala, Waleed S. Alnumay
Summary: In recent years, decentralized applications such as Distributed Ledger Technologies and blockchain have become suitable for secure sharing of information using privacy preserving techniques like zero-knowledge protocols. However, the slow performance of traditional zero-knowledge protocols on big data is a major issue on blockchain ledgers. This paper proposes an improved zero-knowledge ledger that replaces the range-proof technique with a more efficient technique based on improved inner product based zero-knowledge proofs. Additionally, this technique allows aggregation of multiple range-proofs into a single proof, making the current zero-knowledge ledger system more efficient than the existing one.
COMPUTERS & ELECTRICAL ENGINEERING
(2022)
Article
Chemistry, Analytical
Owen Lo, William J. Buchanan, Sarwar Sayeed, Pavlos Papadopoulos, Nikolaos Pitropakis, Christos Chrysoulas
Summary: E-governance aims to simplify processes involving government, citizens, and businesses, and digital technologies can enhance administrative efficiency and trust. However, implementing a distributed data sharing model is challenging. This paper proposes integrating a permissioned blockchain with IPFS to enable citizens to control their relationship with the government.
Article
Computer Science, Hardware & Architecture
Timon Rueckel, Johannes Sedlmeir, Peter Hofmann
Summary: Research shows that the lack of broad adoption of federated machine learning in practice is mainly due to the significant challenge of simultaneously achieving fairness, integrity, and privacy preservation. To address this issue, a FL system that incorporates blockchain technology, local differential privacy, and zero-knowledge proofs is proposed.
Article
Computer Science, Information Systems
Ken Miyachi, Tim K. Mackey
Summary: Off-Chain Blockchain Systems (OCBS) play a critical role in enterprise blockchain solutions by enhancing scalability, reducing data storage requirements, and enhancing data privacy. However, strict regulatory requirements in the healthcare industry limit blockchain adoption. It is crucial to align OCBS design features with different types of healthcare data management to overcome this challenge.
INFORMATION PROCESSING & MANAGEMENT
(2021)
Review
Chemistry, Analytical
Tejal Rathod, Nilesh Kumar Jadav, Mohammad Dahman Alshehri, Sudeep Tanwar, Ravi Sharma, Raluca-Andreea Felseghi, Maria Simona Raboaca
Summary: This paper presents a survey of wireless networks (WNs) in the context of security and privacy issues with blockchain-based solutions. The existing research works, security requirements, and security issues in different generations of WNs are analyzed. The influence of blockchain technology and a taxonomy for blockchain-enabled security solutions in WN are showcased. Furthermore, a blockchain and 6G-based WN architecture is proposed and evaluated against performance metrics. Various open issues and research challenges for blockchain-based WNs solutions are discussed.
Review
Computer Science, Theory & Methods
Hao Li, Chengcheng Li, Jian Wang, Aimin Yang, Zezhong Ma, Zunqian Zhang, Dianbo Hua
Summary: Artificial intelligence (AI) has contributed to the rapid development of healthcare, addressing complex medical problems. However, the lack of standardization in patient electronic medical records and legal and ethical requirements for patient information privacy hinders widespread AI integration. Federated learning, combined with privacy-preserving algorithms, can overcome data fragmentation and improve security and computational efficiency when combined with blockchain and edge computing. This paper reviews recent research on federated learning in healthcare, explores its architectures and classification models, and analyzes its advantages and security risks in medical applications. Standard privacy protection methods are introduced and the current state of federated learning and healthcare applications is discussed, concluding with a summary and future outlook.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2023)
Article
Computer Science, Information Systems
Sujit Biswas, Zigang Yao, Lin Yan, Abdulmajeed Alqhatani, Anupam Kumar Bairagi, Fatima Asiri, Mehedi Masud
Summary: The widespread use of smart devices and city-centric services improves civic life, but also raises concerns about privacy and security. To address security issues, city-centric services are shifting towards blockchain-based systems, which is a time-consuming and challenging process. This paper proposes an interoperability framework for blockchain-based smart city services and explores how independent service providers can continue local transactions without overloading the blockchain network. A simulated interoperability network demonstrates the effectiveness of the framework, showcasing the scalability and memory optimization of the blockchain network.
Review
Chemistry, Multidisciplinary
Haifa Alanzi, Mohammad Alkhatib
Summary: An identity management system (IDMS) is a system that manages and organizes identities and credentials information exchanged between users, identity providers (IDPs), and service providers (SPs) to ensure privacy and security. Traditional IDMS has limitations, such as privacy threats and single point of failure, which can be addressed by blockchain technology.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Information Systems
Narmeen Zakaria Bawany, Tehreem Qamar, Hira Tariq, Saifullah Adnan
Summary: Blockchain technology has the potential to greatly enhance telehealth services by ensuring privacy, security, and trust. This paper presents the BlockHeal framework, which integrates all essential healthcare services and provides a secure and trusted environment.
Article
Computer Science, Information Systems
Md. Ariful Islam, Md. Antonin Islam, Md. Amzad Hossain Jacky, Md. Al-Amin, Md. Saef Ullah Miah, Md. Muhidul Islam Khan, Md. Iqbal Hossain
Summary: This paper proposes a Blockchain-based distributed application platform to protect personal sensitive data of healthcare service providers in Bangladesh. The application framework enables users to securely create digital agreements using data immutability and smart contracts. Hyperledger Fabric and Blockchain are employed to ensure data integrity, privacy, permissions, and service availability.
Review
Chemistry, Multidisciplinary
Matteo Fiore, Angelo Capodici, Paola Rucci, Alessandro Bianconi, Giulia Longo, Matteo Ricci, Francesco Sanmarchi, Davide Golinelli
Summary: This review summarizes the use of blockchain technology in healthcare supply chain management, specifically for drugs, medical devices, and blood, organs, and tissues. A systematic review of 28 articles found that while there is significant interest and diverse ideas and methodologies, real-life applications are still lacking.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Information Systems
Tsung-Ting Kuo, Anh Pham
Summary: This study aims to propose an algorithm-agnostic approach to detect model misconduct in cross-institutional collaborations and apply it to federated machine learning on genomic/healthcare data. The results show that the proposed method has a high recall rate with low computational cost, effectively identifying misconduct.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
(2022)
Article
Computer Science, Information Systems
Tripti Rathee, Parvinder Singh
Summary: This paper is a systematic literature review on Identity Management (IdM) in blockchain. It focuses on reviewing the challenges faced in IdM over the years and how blockchain has addressed these challenges. The paper provides insights into the research trends, challenges, frameworks, initiatives, consensus algorithms, and research projects in the field of IdM using blockchain.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Green & Sustainable Science & Technology
Amit Patwardhan, Adithya Thaduri, Ramin Karim
Summary: The paper discusses the importance of digitalization for achieving operational excellence and meeting stakeholders' needs in the railway industry, emphasizing the critical roles of digital infrastructure and cybersecurity. It also addresses the challenges presented by governance, business, and technical aspects, and provides a taxonomy of issues and challenges for developing a secure and resilient data sharing framework for railway stakeholders.
Article
Computer Science, Information Systems
Asma Belhadi, Youcef Djenouri, Djamel Djenouri, Gautam Srivastava, Jerry Chun-Wei Lin
Summary: This paper presents a novel framework that combines deep learning and decomposition for identifying a group of intrusions in the IoT context. By collecting data and using a recurrent neural network to estimate individual intrusions, the framework then identifies outliers based on a decomposition strategy. Experimental evaluation using two intrusion datasets demonstrates the superiority of the proposed framework over state-of-the-art approaches.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Youcef Djenouri, Asma Belhadi, Gautam Srivastava, Jerry Chun-Wei Lin
Summary: This paper presents a novel and comprehensive framework that combines eXplainable AI (XAI), deep learning, and evolutionary computation to solve various IoT applications. The IoT data from different sensors is transformed into an image database using the Gamian angular field. The images are then trained using VGG16 with the integration of XAI technology and hyper-parameter optimization. Extensive testing on two separate IoT datasets demonstrates the superior performance of the proposed approach in terms of both runtime and accuracy compared to the baseline approaches.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Youcef Djenouri, Asma Belhadi, Anis Yazidi, Gautam Srivastava, Pushpita Chatterjee, Jerry Chun-Wei Lin
Summary: With the increase in smart medical devices and applications in healthcare settings, the use of IoT and intelligent agents for disease detection and healthcare decision-making has become more important. This article presents a collaborative disease detection system based on IoMT and image data, where intelligent agents explore the medical data obtained from smart sensor devices using reinforcement learning to detect diseases. The results of intensive experiments show the significance of using intelligent agents and collaboration in disease detection, surpassing baseline solutions.
IEEE SENSORS JOURNAL
(2023)
Article
Computer Science, Artificial Intelligence
Usman Ahmed, Jerry Chun-Wei Lin, Gautam Srivastava
Summary: This article presents the approach of embedding trajectory deviation points and deep clustering. The proposed learning trajectory embedding approach successfully captures the structural identity and outperforms competing strategies in detecting outliers in the trajectory and deviation locations.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Computer Science, Information Systems
Shuai Liu, Yang Zhang, Gautam Srivastava
Summary: This study proposes a multi-branch attention network and a pseudo-background label generation method to address the problem of temporal action localisation in video understanding. Experimental results show that the proposed method can improve the separation effect of action instances, background, and action context, and achieves excellent performance on the THUMOS-14 dataset.
ENTERPRISE INFORMATION SYSTEMS
(2023)
Article
Engineering, Civil
Debashis Das, Sourav Banerjee, Pushpita Chatterjee, Uttam Ghosh, Utpal Biswas
Summary: In recent years, the corporate and industrial sectors have undergone significant transformations in vehicle-to-vehicle (V2V) communication, using the latest software, hardware, and technologies to develop trusted applications. Various technologies, including sensors, data storage, and communication devices, have been integrated into connected vehicles for V2V communication. Blockchain can help address issues such as data security, user privacy, and vehicle security in V2V communication systems. This paper proposes a secure blockchain-enabled V2V communication system (BVCS) that enhances vehicle security and enables secure data sharing and communication among vehicles, using smart contracts to authenticate users and establish secure communication. The proposed system improves data security, user privacy, and vehicle security, creating a trusted environment in V2V communication systems.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Information Systems
Tianzhu Guan, Gautam Srivastava
Summary: A new multi-frequency communication routing protocol is proposed to improve the average remaining energy of the network, reduce the routing overhead, extend the network lifecycle, and reduce the average end-to-end delay. The protocol constructs a multi-frequency wireless communication network topology and measures and analyzes its routing. The optimal wireless network multi-frequency communication routing protocol is selected using the ant colony algorithm based on the wireless network communication energy consumption model and the wireless network communication data transmission mechanism. The experimental results demonstrate the effectiveness of the protocol in terms of network energy, routing overhead, network lifespan, and end-to-end delay reduction.
Article
Computer Science, Information Systems
Shitharth Selvarajan, Gautam Srivastava, Alaa O. Khadidos, Adil O. Khadidos, Mohamed Baza, Ali Alshehri, Jerry Chun-Wei Lin
Summary: This research aims to implement an Artificial Intelligence-based Lightweight Blockchain Security Model (AILBSM) to ensure privacy and security of IIoT systems. By combining the advantages of lightweight blockchain and AI mechanisms, the proposed model reduces the impact of attacks and transforms features into encoded data using an Authentic Intrinsic Analysis (AIA) model. Extensive experiments validate the improved execution time, classification accuracy, and detection performance of the proposed model.
JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS
(2023)
Review
Management
Gautam Srivastava, Surajit Bag
Summary: This study explores the potential for face recognition and neuro-marketing in modern-day marketing based on an in-depth examination of the extant literature. The findings reveal that these two domains remain understudied and provide insights for managers to design marketing strategies and boost conversion rates.
BENCHMARKING-AN INTERNATIONAL JOURNAL
(2023)
Article
Engineering, Civil
Tongtong Gai, Dehu Yu, Sen Zeng, Jerry Chun-Wei Lin
Summary: Accurate determination of cable force values is crucial for preventing damage to cable bridges. This paper proposes an intelligent method for determining bridge cable force based on the vibration method, which overcomes the challenges of distinguishing boundary conditions and low-order natural frequency. By using cable length, linear density, flexural stiffness, and input frequency as inputs and cable force as the output, a neural network is established to identify the cable force and optimize the model using an intelligent swarm optimization algorithm. Results show that the proposed GRNN optimized by sparrow search algorithm achieves better identification performance compared to other prediction models, with prediction errors within 10% for short cables and within 5% for long cables. This method allows for accurate identification of cable force, disregarding boundary conditions and vibration frequency, and has wide-ranging applications.
ENGINEERING STRUCTURES
(2023)
Article
Engineering, Civil
Youcef Djenouri, Asma Belhadi, Essam H. Houssein, Gautam Srivastava, Jerry Chun-Wei Lin
Summary: This paper presents a novel intelligent system based on graph convolutional neural networks for road crack detection, which achieves high precision by analyzing image features and training models.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Hardware & Architecture
Qing Wei, Qiaoli Lin, Gautam Srivastava
Summary: This paper presents the design of a multimedia platform for digitally estimating agricultural output. By utilizing embedded technology, the platform collects environmental parameters related to agricultural output and utilizes the grey relational Support Vector Machine algorithm for prediction. Experimental results demonstrate that this method accurately predicts agricultural output with high precision and has abundant applications.
MOBILE NETWORKS & APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Yanbei Liu, Shichuan Zhao, Xiao Wang, Lei Geng, Zhitao Xiao, Jerry Chun-Wei Lin
Summary: Graph Neural Networks (GNNs), based on deep learning, have attracted research interest. Many GNNs have achieved state-of-the-art accuracy but lack supervision information for unlabeled data. To address this, we propose SCGNN which extracts self-supervision information from unlabeled nodes and utilizes label information from labeled nodes. Experimental results show that SCGNN outperforms baselines, improving accuracy by an average of 2.08% and by 5.8% on the Disease dataset.
IEEE TRANSACTIONS ON BIG DATA
(2023)
Article
Computer Science, Artificial Intelligence
Denghui Zhang, Muhammad Shafiq, Liguo Wang, Gautam Srivastava, Shoulin Yin
Summary: This study proposes a security scheme suitable for computation-limited devices in IoT, achieving secure and efficient transmission of high-resolution remote sensing images using visual cryptography. The recognition performance of small encryption datasets for remote sensing images is improved by fine-tuning the pre-trained model from large-scale datasets.
CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Ali Ranjha, Muhammad Awais Javed, Gautam Srivastava, Jerry Chun-Wei Lin
Summary: Unmanned aerial vehicles (UAVs) have emerged as potential candidates to support communications in 6G systems, but their usage increases interference. To address this issue, we propose low-complexity algorithms for interference coordination and model different types of interference. Results show that the proposed algorithms achieve better fairness and performance compared to conventional algorithms in UAV communications.
IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY
(2023)
