检索结果-内蒙古大学图书馆

Blockchain in Electronic Voting: A Systematic Review of Security, Scalability, and Emerging Technologies 3

Blockchain in Electronic Voting: A Systematic Review of Secu...

3rd International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Gupta, Shantanu Tyagi, Neha Amity University Amity School of Engineering & Technology Department of Computer Science and Engineering Uttar Pradesh India

ISBN: (纸本)9798331515911

Blockchain technology has emerged as a promising solution for enhancing the security, transparency, and efficiency of electronic voting systems. This review paper presents a comprehensive analysis of recent research papers, examining various cryptographic techniques, consensus mechanisms, and blockchain frameworks designed to address critical issues such as voter anonymity, coercion resistance, and election integrity. The findings are categorized into key themes: security, privacy, scalability, verifiability, and performance, with an emphasis on advanced methods like biometric encryption and quantum key distribution. Emerging trends, including quantum cryptography and decentralized governance, are explored as future avenues for innovation. Despite these advancements, challenges related to governance, user engagement, legal frameworks, and system interoperability persist. The paper concludes by identifying the need for further research into scalability and security improvements, as well as the seamless integration of blockchain solutions with existing electoral infrastructure to enable real-world adoption © 2025 IEEE.

关键词： Anonymity

来源：评论

学校读者我要写书评

暂无评论

Simulated Annealing as a Strategy for Robust Routing in Mobile Ad-hoc Networks 3

Simulated Annealing as a Strategy for Robust Routing in Mobi...

引用

3rd International Conference on Communication, Control, and Intelligent Systems, CCIS 2024

作者： Shukla, Abhishek Abbas Rizvi, Syed Wajahat Kanrar, Soumen Amity University Department of Computer Science and Engineering Uttar Pradesh India Amity University Department of Computer Science and Engineering Jharkhand India

ISBN: (纸本)9798331528201

In this study, we check the performance of traditional AODV (Ad-hoc On-Demand Distance Vector), MAODV (Multicast AODV), and a proposed Simulated Annealing (SA)-Optimized Routing protocol in a Mobile Ad-hoc Network (MANET). A python-based simulation was used to compare these protocols performance in terms of packets sent, packets received, latency, and throughput under dynamic network conditions. These results shows that SA-optimized routing consistently gives improved performance then AODV and MAODV in all performance metrics, achieving significantly higher packet delivery rates and lower latency. In SA-optimized routing adapts effectively to changing network conditions by exploring next to optimal routes early in the simulation and converging to optimal routes over time. This adaptability leads to better throughput, particularly in scenarios with high node mobility, making the SA-optimized routing protocol a more robust way for MANET environments. © 2024 IEEE.

关键词： Simulated annealing

来源：评论

学校读者我要写书评

暂无评论

Enhancing Human Activity Detection and Classification Using Fine Tuned Attention-Based Transformer Models

引用

SN computer science 2024年第8期5卷 1142页

作者： Yadav, Ram Kumar Daniel, A. Semwal, Vijay Bhaskar Department of Computer Science and Engineering Amity University Gwalior India Department of Computer Science and Engineering MANIT Bhopal India

Recognition of human activity is an active research area. It uses the Internet of Things, Sensory methods, Machine Learning, and Deep Learning techniques to assist various application fields like home monitoring, robotics, surveillance, and healthcare. However, researchers face problems such as time complexity, more execution time of the model, and classification accuracy. This paper introduces a novel approach to overcome the issue as mentioned earlier by using the deep learning transformer model such as ViT(Vision Transformer), DieT(Data-efficient image Transformers), and SwinV2 transformer, which are used for image-based datasets (i.e., Standard40, MPII human pose) and VideoMAE transformer is used for video-based UCF101 and HMDB51 datasets. The approaches achieved remarkable accuracy in classifying human activities. Evaluations using the ViT, DeiT, and Swin transformer V2 with Stanford40 are 90.8%, 90.7%, and 88%;similarly, MPII Human Pose datasets show 87%, 85.6%, and 87.1%. In addition, this paper's method has achieved remarkable accuracies of 94.15% and 78.44%, respectively, when applying the VideoMAE transformer to video-based activity recognition on the UCF101 and HMDB51 datasets. These findings emphasize the efficacy of the attention-based transformer (i.e., ViT, DeiT, SwinV2, and VideoMAE) model and the novelty of earlier no-result evaluation on these various datasets with attention-based transformers. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Attention-based transformers Data augmentation Deep learning HAR Machine learning

来源：评论

学校读者我要写书评

暂无评论

A ranking framework for the selection of IoT cloud platforms using hybrid multi-attribute decision-making method

引用

International Journal of Intelligent Computing and Cybernetics 2024年第4期17卷 824-843页

作者： Supriya Raheja Rakesh Garg Ritvik Garg Department of Computer Science and Engineering Amity University Uttar PradeshNoidaIndia Department of Computer Science and Engineering Gurugram UniversityGurugramIndia Department of Computer and Communication Engineering Manipal University JaipurJaipurIndia

Purpose-The Internet of Things(IoT)cloud platforms provide end-to-end solutions that integrate various capabilities such as application development,device and connectivity management,data storage,data analysis and data *** high use of these platforms results in their huge availability provided by different ***,choosing the optimal IoT cloud platform to develop IoT applications successfully has become *** key purpose of the present study is to implement a hybrid multi-attribute decision-making approach(MADM)to evaluate and select IoT cloud ***/methodology/approach-The optimal selection of the IoT cloud platforms seems to be dependent on multiple ***,the optimal selection of IoT cloud platforms problem is modeled as a MADM problem,and a hybrid approach named neutrosophic fuzzy set-Euclidean taxicab distance-based approach(NFS-ETDBA)is implemented to solve the ***-ETDBA works on the calculation of assessment score for each alternative,*** cloud platforms,by combining two different measures:Euclidean and taxicab ***-A case study to illustrate the working of the proposed NFS-ETDBA for optimal selection of IoT cloud platforms is *** results obtained on the basis of calculated assessment scores depict that“Azure IoT suite”is the most preferable IoT cloud platform,whereas“Salesman IoT cloud”is the least ***/value-The proposed NFS-ETDBA methodology for the IoT cloud platform selection is implemented for the first time in this *** is highly capable of handling the large number of alternatives and the selection attributes involved in any decision-making ***,the use of fuzzy set theory(FST)makes it very easy to handle the impreciseness that may occur during the data collection through a questionnaire from a group of experts.

关键词： Internet of things(IoT) Multi-attribute decision-making Neutrosophic fuzzy set Euclidean and taxicab distance

来源：评论

学校读者我要写书评

暂无评论

Proposed AES-based Obfuscation and Encryption Model for Cloud Data Security 1

Proposed AES-based Obfuscation and Encryption Model for Clou...

引用

1st International Conference on Intelligent Systems and Computational Networks, ICISCN 2025

作者： Singh, Prabhdeep Singh, Pawan Agarwal, Abhay Kumar Kumar, Anil Amity School of Engineering and Technology Department of Computer Science and Engineering Lucknow India Kamla Nehru Institute of Technology Department of Computer Science and Engineering Sultanpur India Amity University Amity School of Engineering and Technology Lucknow India

ISBN: (纸本)9798331529246

Cloud Computing (CC) offers a diverse range of services along with huge data storage across a network. CC has collaborated with varied emerging technologies like IoT because of its numerous advantages. Despite CC's benefits, cloud-based servers are not always trustworthy in real-world scenarios. Users' privacy will be compromised if they send their data straight to cloud platforms since crucial information will be exposed to cloud servers. Thereby, this work develops a data security model in the cloud with two stages, proposed secured data storage and proxy re-encryption. Initially, the data is stored securely in the cloud based on improved AES-based encryption as well as obfuscation-based encryption. Based on the request from the data user, proxy re-encryption is done using Kronecker product-based encryption. The enhanced AES achieved the lowest value of 0.025 for the CCA attack with a key size of 128 bits. Thus, the final encoded key is obtained. © 2025 IEEE.

关键词： Cloud platforms

来源：评论

学校读者我要写书评

暂无评论

Dynamic Sign Language Recognition with Hybrid CNN-LSTM and 1D Convolutional Layers 11

Dynamic Sign Language Recognition with Hybrid CNN-LSTM and 1...

引用

11th International Conference on Reliability, Infocom Technologies and Optimization, ICRITO 2024

作者： Gupta, Aakanshi Sawan, Akash Singh, Shivam Kumari, Sandhya Amity University Computer Science and Engineering Noida India

ISBN: (纸本)9798350350357

Our study presents a novel approach for sign language recognition (SLR) using Convolutional Neural Networks (CNN), 1D convolutional layers, and Long Short-Term Memory (LSTM) networks. By integrating CNN and 1D convolutional layers to capture temporal patterns and LSTM layers for handling long-term dependencies, our model achieves accurate classification of sign language gestures. We also discuss future directions, including expanding the model's recognition capabilities to other sign languages and enabling user customization, to enhance inclusivity and user-friendliness within the sign language community. This work contributes to advancing SLR technology and improving communication accessibility for individuals with hearing impairments. © 2024 IEEE.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

A Systematic Review using Blockchain Technology for IOT-Based Health Care Security

A Systematic Review using Blockchain Technology for IOT-Base...

引用

2024 IEEE International Conference on Big Data and Machine Learning, ICBDML 2024

作者： Singh, Kedar Nath Upadhyay, Arvind Kumar Amity University Computer Science and Engineering Gwalior India

ISBN: (纸本)9798350374100

Today, Internet of Things (IoT) data sharing is a big challenge for increasing the progress, efficiency, and effectiveness of any organization in the health sector through IoT-based applications. Generally, health records follow centralized abilities in the IoT. Health sector Data Security and failures of centralized servers are issues in the IoT. Peer-to-peer networks utilize distributed applications and duplicate transactions leveraging digital ledgers in the blockchain. Blochchain is recording all health information on a decentralized system that is impossible to change or hack. Blockchain technology supports IoT privacy, cryptocurrencies, healthcare, smart contracts, supply chain management, identity verification, insurance, etc. IoT-based health records contain a lot of problems like privacy, security, performance, ethics, data ownership, patient access and control, etc. In easy ways, blockchain technology exacerbates these kinds of problems. Ethereum and Hyperledger are supported as frameworks using blockchain technology. Compared to the previously specified data values, IoT-based health data has a significantly higher level of security and privacy. This study explores in detail the various approaches, workings, and technical details used in various languages. © 2024 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Image-based DeepFake Detection Using Artificial Intelligence 14

Image-based DeepFake Detection Using Artificial Intelligence

引用

14th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2025

作者： Singh, Shailendra Kumar Kumar, Gautam Dubey, Aditya Kumar Yadav, Ritik Rai, Vishal Sharma, Anil Department of Computer Science and Engineering Amity University Noida India

ISBN: (纸本)9798331531935

The increasing sophistication of deepfake technology poses significant risks to privacy, security, and public trust in digital media. As a result, deepfake detection has become a critical research area, with artificial intelligence -driven approaches playing a central role. This paper presents a comprehensive analysis of convolutional neural network -based deepfake detection methods, highlighting key challenges such as dataset limitations, social media compression effects, real-time detection constraints, and the rapid evolution of manipulation techniques. While existing detection models demonstrate promising accuracy, challenges remain in terms of generalizability, computational efficiency, and robustness against complex manipulations, including audio and full-body deepfakes. This study explores strategies to enhance detection performance through data augmentation and optimized architectural design. Furthermore, it discusses potential future directions, such as leveraging multimodal analysis, federated learning, and explainable AI, to improve the reliability and adaptability of deepfake detection systems. © 2025 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Techniques for Twitter Spam Detection: Comparative Insights and Real-Time Application 14

Machine Learning Techniques for Twitter Spam Detection: Comp...

引用

14th International Conference on Cloud Computing, Data science and engineering, Confluence 2024

作者： Asthana, Yashvardhan Chhabra, Rahul Srivastava, Sweta Amity University Computer Science and Engineering Noida India

ISBN: (纸本)9798350344837

In today's world of digital communication, platforms like Twitter are essential for connecting people globally. But there's a problem - spam on Twitter can be a big issue for users. Our main goal is to make a system that can spot and stop spam using fancy computer techniques. We looked at many tweets on Twitter, trying to understand how spam and regular tweets are spread out. We found a problem with our data - there were way more regular tweets than spam ones. To fix it, we used something called Synthetic Minority Over-sampling Technique (SMOTE) to make the number of tweets more equal. After that, we made and tested 13 computer models, looking at how good they were using important measures like accuracy and recall. The result is a strong system that can tell the difference between spam and real tweets on Twitter. This helps make online talks better, keeps users safe, and makes sure Twitter stays a good place to be. Since spam tactics keep changing, our work is an important step in making social media safer. This means everyone can enjoy a safer and better time online. © 2024 IEEE.

关键词： Digital communication systems

来源：评论

学校读者我要写书评

暂无评论

Crafting a Machine Learning Model for Discerning Synthetic and Authentic Images 2

Crafting a Machine Learning Model for Discerning Synthetic a...

引用

2nd International Conference on Advances in Computation, Communication and Information Technology, ICAICCIT 2024

作者： Shah, Misha Jaiswal, Gautam Sharma, Dolly Amity School of Engineering and Technology Amity University Noida India Department of Computer Science and Engineering Amity University Noida India

ISBN: (纸本)9798331541217

This paper shows the development of a Convolutional Neural Network (CNN) model with an attention mechanism and data augmentation for discerning synthetic and authentic images. Given the increase in AI-generated content there is a need for robust methods to identify an image's authenticity. The model employs ensemble learning by using ResNet50 and VGG16 architectures which are combined with a custom CNN. The project has detailed explanations of CNNs, data augmentation, TensorFlow, CUDA, ensemble models and the mathematical concepts underlying these techniques. With a dataset of 2.7 million images, the model aims for high accuracy in classification tasks. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：