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The Impact of Blockchain Technology for Evaluation of Electronic Medical Certification

SN computer science 2025年第5期6卷 1-14页

作者： Azam Zia, M. Anwar, Munazza Mehmood, Faisal Razzaq, Abdul Asif, Muhammad Department of Computer Science University of Agriculture Faisalabad Punjab Faisalabad 38000 Pakistan Department of Civil and Transportation Engineering Shenzhen University Shenzhen 518060 China Computer Science Muhammad Nawaz Shareef University of Agriculture Punjab Multan 59300 Pakistan Department of Computer and Software Engineering Information Technology University (ITU) Punjab Lahore Pakistan

Evaluation of Electronic Medical Certification (EMC) is integral to today's healthcare systems since they are a consolidated database of individual patients' medical histories. Security measures and privacy issues are standard in electronic medical certification. Incompatible systems make sharing data across healthcare providers difficult, which may lead to data breaches and a lack of patient authority over their medical data. Blockchain has become essential for real-world corporate applications where confidentiality of information is paramount. The handling of security in medical records through a decentralized peer-to-peer network might be revolutionized by blockchain technology and improving the protection of the interchange of healthcare records. This study proposes a lightweight flask framework-based blockchain strategy to store and display patient status and transaction log information about their disease diagnosis. In a potential Blockchain system, the diseased patients act as assets, and their records contain any prior illnesses as blocks. The report analyzes a lot of national and international EHR standards. It identifies which of these interoperability needs to be addressed, discusses the interoperability challenges in but also outlines the standards. Current blockchain-based EHR frameworks. Without the suggested has the requirement for centralized systems. By using this framework, the healthcare industry can be provided safer ways to while also providing the exchange of health information. It offers features of immutability, security, and user control over stored records. This work contributes to an understanding of what potential Blockchain technology has offered an interoperable application in the EHR frameworks. Meet the blockchain-based EHR framework. Multiple national and international EHR standards. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： Blockchain Cryptography Decentralized Electronic medical certification (EMC) Transaction

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A Combination Model of Periodic and Non-periodic Events for Temporal Knowledge Graph Event Prediction

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Chinese Journal of Electronics 2025年第3期34卷 952-961页

作者： Chen Yue Huang Yongzhong School of Computer Science and Information Security Guilin University of Electronic Technology Guilin 541004 China School of Data Science and Software Engineering Wuzhou University Wuzhou 543002 China

Temporal knowledge graph (TKG) reasoning aims to predict missing facts or future events at given timestamps and has attracted more and more attention in recent years. Existing TKG reasoning methods mainly focus on the interactions between entities and ignore the associations between events where the entities involve. In addition, the characteristics of different types of events have not been studied and exploited, which reduces the performance of event prediction. To address these problems, this paper proposes a combination model of periodic and non-periodic events (CM-PNP). Specifically, there are two basic components designed to process different types of events. The periodic component of CM-PNP learns the recurrent pattern of periodic events and encodes the temporal information in the manner of timespan to prevent the unseen timestamp issue. The non-periodic component of CM-PNP introduces extra information (e.g., entity attributes) to represent non-periodic events, and predicts this type of events according to the related historical events. A combination model of multiple sub-models that focus on encoding different parts of the event is used to improve the performance of single model. The periodic and non-periodic components are combined by a gate block. The experimental results on three real-world datasets demonstrate that CM-PNP outperforms the existing baselines.

关键词： Temporal knowledge graph Temporal knowledge graph reasoning Event prediction Embedding learning Data mining

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VCApather: A Network as a Service Solution for Video Conference Applications 34

VCApather: A Network as a Service Solution for Video Confere...

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34th Workshop on Network and Operating System Support for Digital Audio and Video, NOSSDAV 2024

作者： He, Dongbiao Lin, Canshu Yu, Xian Westphal, Cedric Ming, Zhongxing Cui, Laizhong Zhou, Xu Garcia-Luna-Aceves, J.J. Sangfor Technologies Inc China College of Computer Science and Software Engineering Shenzhen University China Computer Network Information Center Chinese Academy of Sciences China China Electrical and Computer Engineering Department University of Toronto Canada Futurewei

ISBN: (纸本)9798400706134

We propose a network service as a solution for video conference applications by constructing network layer routing strategies. Our approach takes into account the characteristics of conferencing flows, addresses various self-customized metrics, and proactively ensures a positive user experience by preventing contention. The performance of VCApather is evaluated using a fully-meshed topology with five nodes and real-world video conference traffic. The results show that VCApather is capable of achieving high link utilization and balance, while also meeting predefined user metrics. Compared to other schemes, VCApather was found to satisfy 69.8% more QoE requirement and to yield an average bitrate improvement of 1.74×. © 2024 ACM.

关键词： Network layers

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Fast Super-Resolution Network via Dynamic Path Selection 2

Fast Super-Resolution Network via Dynamic Path Selection

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2nd International Conference on Image Processing, computer Vision and Machine Learning, ICICML 2023

作者： Jia, Longfei Hu, Yuguo Tian, Xianlong Luo, Wenwei University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu China University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu China

ISBN: (纸本)9798350331417

In the context of edge computing environments, where the storage space and computational resources are constrained, complex super-resolution network models face significant challenges during inference. In this paper, we propose a Fast Super-Resolution Network (FSRN) based on the dynamic path selection mechanism. This method employs a policy network to boost the inference process of super-resolution network models, enabling efficient super-resolution tasks under resource limitations. The primary function of the policy network is to intelligently select appropriate inference paths based on input data and available computational resources. Its key objective is to minimize the degradation in super-resolution quality while reducing the computational burden as much as possible. In view of this objective, we designed a reward function to guide the policy network in discovering the optimal strategies. With the guidance of the policy network, we successfully enhanced the inference speed of super-resolution network models on edge devices while efficiently reducing computational overhead. Extensive experiments verify that the proposed method can significantly reduce the inference time at the cost of slight or even no performance degradation. © 2023 IEEE.

关键词： accelerate reasoning edge computing resource constrained Super-resolution

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A Robust Key Exchange and Tamper-Resistant Protocol for HAN and NAN Networks in Smart Grids

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IEEE Internet of Things Journal 2025年第12期12卷 21394-21403页

作者： Ayub, Muhammad Faizan Li, Xiong Mahmood, Khalid Shamshad, Salman Das, Ashok Kumar Wang, Guijuan University of Electronic Science and Technology of China School of Computer Science and Engineering Sichuan Chengdu611731 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan The University of Lahore Department of Software Engineering Lahore54590 Pakistan International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500 032 India Korea University College of Informatics Department of Computer Science and Engineering Anam-ro Seoul145 Korea Republic of Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan250353 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Industrial Network and Information System Security Jinan250353 China

Smart Grids (SG) rely on Home Area Networks (HAN) and Neighborhood Area Networks (NAN) to ensure efficient power distribution, real-time monitoring, and seamless communication between smart devices. Despite these advantages, the use of public communication channels in HAN and NAN networks introduces critical challenges, such as vulnerability to impersonation, physical tampering, and scalability issues in resource-constrained environments. These issues compromise the stability, reliability, and security of SG environments. Existing protocols often fail to adequately address these challenges, particularly in ensuring resistance to physical tampering of supply lines and impersonation attacks. Additionally, they struggle to minimize the computation, communication, and energy costs associated with securing a resource-constrained SG environment. Therefore, we propose a robust key exchange and tamper-resistant protocol for HAN and NAN networks to address these limitations. The proposed protocol leverages the Physical Unclonable Function (PUF) mechanism to offer physical tampering resistance to smart meters. We validate our protocol formally using the Random or Real (RoR) model, which confirms its security robustness. Additionally, our informal security analysis highlights the protocol's resilience against impersonation, physical tampering attacks, etc. We analyze and compare the performance of the proposed protocol, which further demonstrates our protocol's effectiveness and security compared to competing protocols. Moreover, the proposed protocol achieves resource efficiency with 45.99% and 58.85% substantial reductions in computation overhead and energy overhead, respectively, compared to competing protocols. These results showcase the protocol's enhanced security and practicality for resource-constrained SG environments. © 2014 IEEE.

关键词： Authentication Protocol

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A Review of Lightweight Security and Privacy for Resource-Constrained IoT Devices

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computers, Materials & Continua 2024年第1期78卷 31-63页

作者： Sunil Kumar Dilip Kumar Ramraj Dangi Gaurav Choudhary Nicola Dragoni Ilsun You Department of Computer Science and Engineering National Institute of Technology JamshedpurJamshedpurIndia School of Computing Science and Engineering VIT University BhopalBhopal466114India Center for Industrial Software The Maersk Mc-Kinney Moller InstituteUniversity of Southern DenmarkSonderborgOdenseDenmark Department of Applied Mathematics and Computer Science Technical University of DenmarkLyngby2800Denmark Department of Information Security Cryptologyand MathematicsKookmin UniversitySeoulSouth Korea

The widespread and growing interest in the Internet of Things(IoT)may be attributed to its usefulness in many different *** settings are probed for data,which is then transferred via linked *** are several hurdles to overcome when putting IoT into practice,from managing server infrastructure to coordinating the use of tiny *** it comes to deploying IoT,everyone agrees that security is the biggest *** is due to the fact that a large number of IoT devices exist in the physicalworld and thatmany of themhave constrained resources such as electricity,memory,processing power,and square *** research intends to analyse resource-constrained IoT devices,including RFID tags,sensors,and smart cards,and the issues involved with protecting them in such restricted *** lightweight cryptography,the information sent between these gadgets may be *** order to provide a holistic picture,this research evaluates and contrasts well-known algorithms based on their implementation cost,hardware/software efficiency,and attack resistance *** also emphasised how essential lightweight encryption is for striking a good cost-to-performance-to-security ratio.

关键词： IoT a sensor device lightweight cryptography block cipher smart card security and privacy

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A Novel Automatic Prompt Tuning Method for Polyp Segmentation

A Novel Automatic Prompt Tuning Method for Polyp Segmentatio...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Jing, Xin Zhou, Heyang Mao, Keming Zhao, Yuhai Chu, Liangyu Northeastern University Software College Shenyang China Northeastern University College of Computer Science and Engineering Shenyang China Northeastern University College of Medicine and Biological and Information Engineering Shenyang China

ISBN: (纸本)9798350386226

Accurate polyp segmentation of colonoscopy images is crucial for diagnosing and treating colorectal cancer. A new type of method for this challenging task has been introduced with the emergence of large vision models like the Segment Anything Model (SAM). However, the application of SAM to medical image segmentation falls short of clinical requirements. In efforts to tailor SAM for medical imaging tasks, researchers often work on improving adapters and prompts separately, over-looking the potential for synergy between them. Furthermore, existing methods still do not overcome the influence of prompt type, quantity, and positioning on segmentation results. SAM's dependency on professionally annotated prompts further limits its utility. To tackle these issues, we propose a fine-tuning strategy named Automatic Prompt Tuning (APT), which aims to generate prompts automatically. This approach begins with adapting SAM for polyp segmentation by incorporating lightweight adapters into the image encoder. Next, we introduce an automatic prompt generator to process features and produce relevant prompts. Finally, we ensure the mask decoder consistently delivers accurate segmentation by leveraging these automatically generated prompts. Extensive experiments on three major polyp segmentation datasets demonstrate that APT outperforms other state-of-the-art approaches, proving its effectiveness. © 2024 IEEE.

关键词： Medical imaging

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A Novel Blockchain-Based Deepfake Detection Method Using Federated and Deep Learning Models

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Cognitive Computation 2024年第3期16卷 1073-1091页

作者： Heidari, Arash Navimipour, Nima Jafari Dag, Hasan Talebi, Samira Unal, Mehmet Department of Software Engineering Haliç University Istanbul34060 Turkey Department of Computer Engineering Kadir Has University Istanbul Turkey Future Technology Research Center National Yunlin University of Science and Technology Yunlin Douliou64002 Taiwan Department of Information Technology Kadir Has University Istanbul Turkey Department of Computer Science University of Texas at San Antonio San AntonioTX United States Department of Computer Engineering Nisantasi University Istanbul Turkey

In recent years, the proliferation of deep learning (DL) techniques has given rise to a significant challenge in the form of deepfake videos, posing a grave threat to the authenticity of media content. With the rapid advancement of DL technology, the creation of convincingly realistic deepfake videos has become increasingly prevalent, raising serious concerns about the potential misuse of such content. Deepfakes have the potential to undermine trust in visual media, with implications for fields as diverse as journalism, entertainment, and security. This study presents an innovative solution by harnessing blockchain-based federated learning (FL) to address this issue, focusing on preserving data source anonymity. The approach combines the strengths of SegCaps and convolutional neural network (CNN) methods for improved image feature extraction, followed by capsule network (CN) training to enhance generalization. A novel data normalization technique is introduced to tackle data heterogeneity stemming from diverse global data sources. Moreover, transfer learning (TL) and preprocessing methods are deployed to elevate DL performance. These efforts culminate in collaborative global model training zfacilitated by blockchain and FL while maintaining the utmost confidentiality of data sources. The effectiveness of our methodology is rigorously tested and validated through extensive experiments. These experiments reveal a substantial improvement in accuracy, with an impressive average increase of 6.6% compared to six benchmark models. Furthermore, our approach demonstrates a 5.1% enhancement in the area under the curve (AUC) metric, underscoring its ability to outperform existing detection methods. These results substantiate the effectiveness of our proposed solution in countering the proliferation of deepfake content. In conclusion, our innovative approach represents a promising avenue for advancing deepfake detection. By leveraging existing data resources and the power of FL

关键词： Blockchain

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Adaptive Climbing Strategy of Snake Robot Based on Compliance Control 4

Adaptive Climbing Strategy of Snake Robot Based on Complianc...

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4th International Symposium on Intelligent Robotics and Systems, ISoIRS 2024

作者： Yang, Huizhuo Dong, Jiyuan Wang, Meng Meng, Shiyong Yang, Lei Xue, Jiashuo Tiangong University School of Electronic and Information Engineering Tianjin China Tiangong University Department of Computer Science and Technology Tianjin China Tiangong University Department of Software Engineering Tianjin China

ISBN: (纸本)9798350364798

Snake robots, exhibiting a high degree of redundancy, are a class of biomimetic robots capable of forming a helical rolling gait for climbing trees and pipes. The surface structure of naturally grown trees is irregular, which may hinder the snake robots from achieving optimal surface conformation. Additionally, the presence of numerous branching structures in pipes introduces unpredictability in pipe climbing. To address these challenges, we propose an adaptive climbing strategy for snake robots based on compliant control. By adjusting a pre-set elasticity coefficient, the snake robot modulates the output torque of each joint, thereby altering the target angle of the joint. This adjustment enables the snake robot to adapt to unstructured environments. We conducted an experiment on climbing curved pipes to verify the effectiveness of this method. The result demonstrate that under unknown conditions, the robustness of the snake robot's climbing motion is enhanced by modifying the pre-set elasticity coefficient based on compliant control. This finding underscores the potential of compliant control in improving the adaptability and performance of Snake robots in complex environments. © 2024 IEEE.

关键词： Microrobots

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Advanced Bearing Fault Diagnosis Using Cuckoo Optimization and KAN Algorithms 4

Advanced Bearing Fault Diagnosis Using Cuckoo Optimization a...

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4th International Conference on Electronic information engineering and computer science, EIECS 2024

作者： Wang, Lingchao Ai, Qiang Yan, Hailong Hao, Ming Li, Xiaoxin School of Information Engineering Liaoning Institute of Science and Engineering Jinzhou China College of Computer Qinghai Normal University Xining China Software College Liaoning Technical University Huludao China

ISBN: (纸本)9798331531409

This study proposes a bearing fault diagnosis method that combines the Cuckoo Optimization Algorithm (COA) with the KAN algorithm. COA, as an intelligent optimization algorithm, is primarily used to find the optimal hyperparameters of the model, thereby enhancing the efficiency and robustness of the diagnosis model. The KAN algorithm is employed to build an intelligent classification model, achieving accurate recognition of multiple fault modes. Experimental results show that the proposed method maintains high diagnostic accuracy even with limited data, providing an effective solution for bearing fault diagnosis. © 2024 IEEE.

关键词： Fault detection

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