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An Enhanced Linearly Homomorphic Network Coding Signature Scheme for Secure Data Delivery in IoT Networks

IEEE Transactions on Information Forensics and Security 2025年 20卷 5534-5548页

作者： Huang, Hao Wang, Xiaofen Au, Man Ho Cao, Sheng Zhao, Qinglin Yu, Jiguo University of Electronic Science and Technology of China Chengdu611731 China The Hong Kong Polytechnic University Department of Computing Hong Kong Hong Kong Macau University of Science and Technology School of Computer Science and Engineering China

Recently, Li et al. proposed an identity-based linearly homomorphic network coding signature (IB-HNCS) scheme for secure data delivery in Internet of Things (IoT) networks, and they claimed that the IB-HNCS scheme can resist pollution attacks. However, this paper shows that the IB-HNCS scheme is vulnerable to pollution attacks, as anyone who only has the public parameter can forge a new file identifier or a valid signature on a corrupted data packet to pollute legitimate sensor data. To enhance security and performance in network coding-based IoT networks, we propose a secure and efficient certificateless linearly homomorphic network coding signature scheme for IoT data delivery, which is free of burdensome certificate management and key escrow issue. In addition, our scheme is proved to be secure against adaptive chosen identity and adaptive chosen subspace attacks under two types of adversaries in the algebraic group model and random oracle model. Therefore, our scheme can verify the validity of data packets and allow data packets to be computed, so as to resist pollution attacks. The performance evaluation demonstrates that our scheme is more efficient and practical than existing secure schemes. Specifically, for a 73-dimensional data vector, the costs of signature generation and verification in our scheme are reduced by 38.588%-86.076% and 38.570%-85.664% respectively under the symmetric bilinear pairing setting, and the costs of signature generation and verification in our scheme are reduced by 17.740%-49.752% and 29.697%-58.645% respectively under the asymmetric bilinear pairing setting. © 2005-2012 IEEE.

关键词： Internet of things

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Environmental Monitoring using LoRa and NodeMCU 3

Environmental Monitoring using LoRa and NodeMCU

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3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Mihir, D.V.S. Pavan, Baramkula Vishnu Datta Aralaguppi, Yogen Avinash Nair, Pranav Biju Belwal, Meena Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

Monitoring of environmental parameters in areas with a sparsely populated and less infrastructure is quite challenging due to issues such as high power consumption, limited range for transmission, and lack of scalability. The innovation of the system proposed here deals with these problems using an IoT-based monitoring system, using LoRa technology and NodeMCU microcontrollers. It can collect and transmit real-time data on temperature, humidity, air quality, and sound levels efficiently. Key outcomes of this research work are reliable range communication up to 2 km under line-of-sight conditions, minimal power consumption, and robust data integrity through sensor calibration and error-checking mechanisms. The solution, which is scalable and low-cost, is proven feasible in real-world applications, particularly in remote and underserved areas, and promises a great future enhancement, including range extension and energy harvesting. © 2025 IEEE.

关键词： Environmental monitoring

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Heart Disease Prediction Analysis with Machine Learning 3

Heart Disease Prediction Analysis with Machine Learning

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3rd International Conference on Disruptive Technologies, ICDT 2025

作者： Mannat Manocha, A. Kumar, Amit Singh, Vivek Kumar Singh, Yuddhvir School of Computing Science and Engineering Galgotias University Uttar Pradesh Gautam Buddha Nagar India

ISBN: (纸本)9798331519582

When early diagnosis and treatment of heart diseases becomes increasingly challenging. However, various studies and researches discovered that recent development in technologies affects the healthcare industry with the advanced machine learning techniques. A machine learning predictive model (LumenCardia) for heart-diseases based on relative parameters is the aim of this work. In this project, we had employed the dataset called Cleveland heart disease dataset, which includes 14 distinct heart disease-related factors. In this study we had applied ML techniques like Random Forest, Logistic Regression, KNN, and Decision Tree to our model. We also looked for relationships among different features in our dataset using conventional ML techniques. The outcome demonstrates that Random Forest produces predictions with more accuracy (93.18%) in less time than other machine learning algorithms. The medical professionals may find LumenCardia beneficial as a decision support system. © 2025 IEEE.

关键词： Logistic regression

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Survey and Tutorial on Hybrid Human-Artificial Intelligence

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Tsinghua science and Technology 2023年第3期28卷 486-499页

作者： Feifei Shi Fang Zhou Hong Liu Liming Chen Huansheng Ning School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China School of Computer Science and Software Engineering East China Normal UniversityShanghai 200062China Faculty of Computing Ulster UniversityNewtownabbey BT370QBUK

The growing computing power,easy acquisition of large-scale data,and constantly improved algorithms have led to a new wave of artificial intelligence(AI)applications,which change the ways we live,manufacture,and do *** with this development,a rising concern is the relationship between AI and human intelligence,namely,whether AI systems may one day overtake,manipulate,or replace *** this paper,we introduce a novel concept named hybrid human-artificial intelligence(H-AI),which fuses human abilities and AI capabilities into a unified *** presents a challenging yet promising research direction that prompts secure and trusted AI innovations while keeping humans in the loop for effective *** scientifically define the concept of H-AI and propose an evolution road map for the development of AI toward *** then examine the key underpinning techniques of H-AI,such as user profile modeling,cognitive computing,and human-in-the-loop machine ***,we discuss H-AI’s potential applications in the area of smart homes,intelligent medicine,smart transportation,and smart ***,we conduct a critical analysis of current challenges and open gaps in H-AI,upon which we elaborate on future research issues and directions.

关键词： hybrid human-artificial intelligence(H-AI) Internet of Things(IoT) artificial intelligence(AI)

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Real-Time Performance Analysis of Multi-Armed Bandit Solution for OBSS and Dynamic Channel Bonding in WLAN 7

Real-Time Performance Analysis of Multi-Armed Bandit Solutio...

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7th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2025

作者： Remya, P.R. Govindarajan, J. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798331507022

Rapid expansion of dense Wi-Fi network deploy-ments creates challenges in optimizing performance. Existing multi-armed bandit (MAB) solutions for dynamic channel bonding (DCB) and overlapping basic service set (OBSS) issues are tested using simulations. This research aims to identify the gaps in current solutions through real-time performance analysis. Along-side this primary objective, we proposed a modified exploration-first algorithm to minimize convergence time. This secondary objective helped us achieve the primary objective. The results demonstrate that our algorithm can adapt to dynamic Wi-Fi environments and improve the user experience. We also present a summary of the inferences from the primary objective study. © 2025 IEEE.

关键词： Dynamic Channel Bonding Exploration-First MAB OBSS WLAN

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Fall Detection using LiDAR Sensor with PointNet++ 4

Fall Detection using LiDAR Sensor with PointNet++

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4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Ayyagari, Anish Sai Ahmed, Syed Ashfaq Venkatakrishnan, Shri Thangavel, Senthil Kumar Jeyakumar, G. Nalluri, Madhusudana Rao Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (纸本)9798331523923

In today's world, fall incidents pose a significant risk to the elderly, often resulting in severe consequences. Falls can cause damage to the body, especially in elders, where it can be *** is vital to detect falls in order to provide assistance. The simple solution is to install cameras in required areas, which would constantly monitor the area for any falls occurring, this poses a privacy issue in high-risk regions such as bathrooms and toilets. Keeping this in mind, this paper proposes the use of LiDAR sensors that do not cause any invasion of privacy for fall detection. The paper further uses the Pointnet++ to detect fall from the LiDAR scans. The model achieves an accuracy of 85.1 % and precision of 84.8 % on a 70-30 split of the dataset and an accuracy of 86.3 % and precision of 86.2 % on an 80-20 split of the dataset. © 2025 IEEE.

关键词： Fall detection

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Chronic Kidney Disease Analysis using Various Biological Parameters under Machine Learning Techniques 3

Chronic Kidney Disease Analysis using Various Biological Par...

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3rd International Conference on Automation, computing and Renewable Systems, ICACRS 2024

作者： Suresh, M. Nirmala, E. Maragatharajan, M. Yadav, Manish School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh Kotri Kalan India School of Computing Science engineering and Artificial Intelligence VIT Bhopal University Madhya Pradesh Kotri Kalan India

ISBN: (纸本)9798331532420

Kidney chronic disease (KCD) has become one of the most critical illnesses which should be diagnosed properly within a certain limit of time for better treatment. Nowadays different algorithms being used for treatment of patients. By using the best predictory model, doctor can easily predict the disease on time. For this verdict, Kidney Chronic Disease Prediction has been discussed in this article. In this article various datasets have been used by the different article authors to predict the disease which are pre-processed with different methods like Univariate Feature Selection (UFS) and Recursive Feature Elimination (RFE), Data mining techniques, etc. which are further used to train and test various ML models get the accuracy by predictory models. The scores gained by the predictory models is then validated to check the precision of the output accuracy of by the model using methods like performance matrices, various cross validation techniques, Mathew Correlation Coefficient (MCC). This whole article is all around the analyses of different articles based on the machine learning and validation techniques with respect to the accuracy. Most of the models attained the accuracy of 99 percent and above. In this article, along with machine learning models it also discussed about two neural networks, which attained the accuracy between 93 to 98% with a good precision value. © 2024 IEEE.

关键词： Adversarial machine learning

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UNet-VT: Integrating U-Net and Vision Transformers for Enhancing Brain Tumor Segmentation in MRI scans 3

UNet-VT: Integrating U-Net and Vision Transformers for Enhan...

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3rd International Conference on Machine Learning and Data engineering, ICMLDE 2024

作者： Kannan, Srinidhi Suryamritha, M. Balaji, Varshini Singh, Rimjhim Padam Department of Computer Science Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

The earlier detection of brain tumour with enhanced accuracy has revolutionized medical image analysis leading to efficient diagnosis and real time patient treatment. Several DL-based methods have been proposed when it comes to extracting important features from an MRI image. Hence, in the present study, the investigators develop a new architecture, termed as UNet-VT using Brain Tumor Image Segmentation Benchmark (BRATS) 2020 to segment the tumor more automatically. To achieve the exact type of segmentation for the comparative performance analysis, a few other recent models have also been trained. Hence, the findings offer enhanced clinical and research use by providing accurate tumor segmentation. This makes it easier to plan for each patient since it assures that the course of treatment can be altered depending on features of each tumor. All in all, UNet-VT can be considered one of the best models for brain tumor segmentation with the highest scores of Dice coefficient 80.45% and mean IOU 89.5%.Thus, the higher segmentation accuracy and reliability of the proposed method can facilitate the development of the custom treatment plans and thereby constitutes a valuable tool for researchers and clinicians. © 2024 The Authors. Published by ELSEVIER B.V.

关键词： Image segmentation

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Securing Wireless Communication: A Comprehensive Arduino-based Approach 3

Securing Wireless Communication: A Comprehensive Arduino-bas...

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3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Navaneeth, M. Vamsi Krishna, K. Belwal, Meena Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

This research aims at developing Arduino solutions to improve the security of wireless communication systems for this work and to present a broad intervention plan for achieving this aim. Incorporating the features of Arduino microcontrollers the system has the potential of mitigating some of the weak wireless communications paradigms. The methodology consists in applying the use of such measures as the encryption algorithms and authentication and the use of secure data transmission protocols. The approach, proposed, not only enhances the security of wireless communication but also is cost effective and easy to install. In this respect, it is hoped that the outcomes of the project will offer effective and efficient solutions for implementing quality security elements for wireless transmission with practical and experimental *** purpose of this work is to generate and transmit the text message through a wireless communication system in a secured way. This facility prevails in the mobile network for which the user pays for it, whereas the system designed here can be used as personal communication system and information can be transmitted at free of *** result of the work is expected to be a secure information transmission with wireless technology implemented and encrypt the data that need to be transmitted without letting interception of a third party and reach the destination, convert and decrypt the message into readable *** work more particularly targets at reducing some of the risks associated with present wireless communication systems through use of effective encryption and authentication. The results are expected to include a major decrease in the interception risks, as well as the effective and safe text message transmission with real-world evidence as proof. © 2025 IEEE.

关键词： Microcontrollers

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Exploring the Cut-Off Between Energy Balance and Delay in In-Network Data Aggregation (I-NDA) for Wireless Sensor Networks 2

Exploring the Cut-Off Between Energy Balance and Delay in In...

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2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Kumar, Anuj Kant Agrawal, Krishna School of Computing Science & Engineering Galgotias University Greater Noida India Ajay Kumar Garg Engineering College Department of Computer Science Engineering Ghaziabad India School of Computing Science & Engineering Galgotias University Yamuna Expressway Gautam buddh Nagar Greater Noida India

ISBN: (纸本)9798350371055

In WSN, data aggregation is an important part of the data collection process. It is used to reduce network traffic and reduce energy consumption. However, this process comes with a cut-off between energy balance and delay. This cut-off is due to the competing interests of the nodes in the network: the sensors require energy to transmit data, while the sinks require low delays in data collection. In order to maintain energy balance and reduce delay, the system must select suitable methods of data aggregation that are both energy-efficient and low-delay. To reduce energy consumption, the system can use energy-conserving data aggregation protocols, such as clustering and tree-structured routing. To reduce delay, they system can use low-delay data aggregation techniques, such as time synchronization and distributed aggregation. By understanding the cut-off between energy balance and delay in I-NDA, it is possible to make informed decisions on the selection of suitable protocols and techniques to ensure energy-efficiency and low-delay data collection. It is important to select the right set of protocols and techniques to balance the efficiency and delay parameters. © 2024 IEEE.

关键词： clustering cut-off data networks sensor traffic wireless

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