检索结果-内蒙古大学图书馆

PUF-Based Privacy-Preserving Simultaneous Authentication Among Multiple Vehicles in VANET

IEEE Transactions on Vehicular technology 2024年第5期73卷 6727-6739页

作者： Awais, Syed Muhammad Yucheng, Wu Mahmood, Khalid Akram, Muhammad Wahid Hussain, Shafiq Das, Ashok Kumar Park, Youngho Chongqing University School of Microelectronics and Communication Engineering Chongqing400044 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin64002 Taiwan University of Lahore Department of Software Engineering Punjab Lahore54590 Pakistan University of Sahiwal Department of Computer Science Punjab Sahiwal57000 Pakistan International Institute of Information Technology Center for Security Theory and Algorithmic Research Telangana Hyderabad500032 India Kyungpook National University School of Electronics Engineering Daegu41566 Korea Republic of

The intellectual and immense attainment of a smart city and auto-mobile vehicles are gradually growing. This growth drives Vehicular Ad-Hoc Network (VANET), a broadly operated complex network for inter-vehicular transmission to acquire information relevant to the vehicle location, road condition, traffic congestion, and speed. Generally, this information is procured through an open-source communication, which is susceptible to various security threats. In broad terms, the privacy of data in VANET is considered an imperative task. In this regard, many authentication protocols are formerly initiated for VANET. Most of these protocols are precarious owing to eavesdropping, replay, and impersonation attacks, etc. Furthermore, most existing protocols operates on enormous communication and computation rate, which turns them inadequate for VANET. This paper exhibits a lightweight privacy-preserving authentication protocol for n number of vehicles in VANET using the physical unclonable function (PUF) technique, and offers efficient and secure communication via public channels. Moreover, we evaluate our protocol formally and informally, showing that it is scalable, lightweight, and safe compared to formerly protocols. The rate of computation and communication is less than most related protocols. We also simulate the proposed scheme using the NS-3 simulator to measure its various network performance parameters. As a result, it is apparent through the beheld statistics that the presented protocol is beyond practical, efficient, and reliable for the secure dissemination of information in VANET. © 1967-2012 IEEE.

关键词： Vehicular ad hoc networks

来源：评论

学校读者我要写书评

暂无评论

Enhancing hydrogen sorption in MgH_(2) by controlling particle size and contact of Ni catalysts

引用

Rare Metals 2021年第4期40卷 995-1002页

作者： Ting-Zhi Si Xue-Yang Zhang Jing-Jing Feng Xiao-Li Ding Yong-Tao Li School of Materials Science and Engineering Anhui University of TechnologyMaanshan 243002China

A comparative study based on MgH2 ball-milled with altered Ni particle sizes under different conditions was conducted to reveal the effect of close contact between hydrides and metal catalysts on their hydrogen sorption *** is found that the Mg+nano-Ni(5 at%)composites not only exhibit a substantial decreased onset desorption temperature by approximately 180℃ but also dramatically enhance the absorption kinetics by sixteen times in comparison with those of pure MgH_(2).This remarkable kinetics enhancement can be explained by the superior catalytic effect of Ni present in composites that highly depends on its particle size and its close contact with MgH2.

关键词： Hydrogen storage Magnesium hydride Nickel Sorption properties Catalytic effect

来源：评论

学校读者我要写书评

暂无评论

An Automated Model for Predicting Weekly Tea Auction Prices at Colombo Tea Auction for Specific Elevations and Grades 6

An Automated Model for Predicting Weekly Tea Auction Prices ...

引用

6th International Conference on Advancements in Computing, ICAC 2024

作者： Ariyaratne, Chandika Arachchi, Samantha Mathara Pallewatta, Pandula Karunanayaka, Kasun Seneviratne, Gihan Halloluwa, Thilina University of Colombo School of Computing Colombo Sri Lanka Nanjing University of Information Science and Technology Nanjing China The University of Queensland School of Electrical Engineering and Computer Science Australia

ISBN: (纸本)9798331517878

Sri Lanka's tea business has existed since the 1800s and maintains a high standard worldwide. However, rivalry is increasing as more competitors enter the market, and tea exporters strive to make their operations more cost-effective. The discovery led to the development of a weekly tea price auction prediction model for a selected tea grade, Broken Orange Pekoe Fannings (BOPF), across different elevations. The existing research suggested using Box and Jenkins models over Machine Learning (ML) models such as Artificial Neural Networks (ANN) and Convolution Neural Networks (CNN). The research also suggested using external factors to improve accuracy. Supply, Demand, and Rainfall were the primary factors. This analysis required data from multiple sources to be combined into one dataset for model building. The tea auction data was from another source, but the rest was in the public domain. For the fourth elevation, the research group employed the SARIMAX variation of Box and Jenkins models to analyze them separately. The results ranged from a Mean Absolute Percentage Error (MAPE) of 0.26% to 6.03%, a manageable and acceptable level of risk. For structured Comma Separated (CSV) file inputs, a new function was created to easily extract predictions from the generated model, improving model usability. © 2024 IEEE.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

Fuzz Testing of UAV Configurations Based on Evolutionary Algorithm 3rd

Fuzz Testing of UAV Configurations Based on Evolutionary Alg...

引用

3rd EAI International Conference on Blockchain technology and Emerging Applications, BlockTEA 2023

作者： Ma, Yuexuan Yu, Xiao Li, Yuanzhang Zhang, Li Yan, Yifei Tan, Yu-An School of Computer Science and Technology Shandong University of Technology Shandong Zibo255049 China School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Department of Media Engineering Communication University of Zhejiang Zhejiang Hangzhou310018 China

ISBN: (纸本)9783031600364

With the widespread application of Unmanned Aerial Vehicle (UAV) technology, its security issues have also attracted much attention, among which the configuration attack against the UAV flight control system is one of the current research hotspots. Attackers always upload seemingly normal configuration combinations and cause an imbalance in the UAV state by exploiting configuration item verification vulnerabilities. This paper accumulates flight data through simulation, generates configuration combinations within the security range using differential evolution-based fuzz testing, uses neural networks to guide configuration item variants, and applies these configuration combinations to the AutoTest of UAV flight control systems. The experimental results show that the configuration combinations generated by fuzz testing can guide the UAV to course deviation, spin, crash and other unstable states;the code coverage and function coverage of the position and attitude code library base in the flight control system have also reached a high level. © ICST Institute for computer sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Optimization

来源：评论

学校读者我要写书评

暂无评论

Remote Sensing Image Segmentation of Wetlands in Macau Based on Machine Learning

Remote Sensing Image Segmentation of Wetlands in Macau Based...

引用

2023 International Conference on Big Data, Information and Intelligent engineering, BDIIE 2023

作者： Li, Cheng Cui, Hanwen Tian, Xiaolin School of Computer Science and Engineering Faculty of Innovation Engineering Macau University of Science and Technology 999078 China School of Computer Science Zhuhai College of Science and Technology Zhuhai519041 China State Key Laboratory of Lunar and Planetary Sciences Macau University of Science and Technology 999078 China

Wetlands are essential components of our natural ecosystems, performing critical functions that contribute to biodiversity conservation, water purification, climate regulation, and shoreline protection. Remote sensing classification of wetlands, wetland resource surveys and other wetland research is booming, for the development of environmental protection policies continue to provide reliable data. Macau is a coastal city with rich wetland resources, but there is no relevant research on wetlands in Macau. In this paper, we use the high spatial resolution remote sensing data from Gaofen-2 satellite to extract the wetlands of Macau SAR to fill the gap of related research. This paper used two distinct machine learning classifiers, including Random Forest (RF) and Support Vector Machine (SVM), to analyse the high spatial resolution remote sensing data of GF-2 satellite in order to extract wetlands in Macau Special Region Area. In this research, the accuracy of RF model is much higher than that of SVM model, comparing the indexes of overall accuracy (OA) and Kappa coefficient. After analysing the resultant images generated after segmentation, the image segmentation result of RF model is better than that of SVM model. As for the RF model, the overall accuracy (OA) is 0.9941 and Kappa coefficient is 0.9899. © Published under licence by IOP Publishing Ltd.

关键词： Wetlands

来源：评论

学校读者我要写书评

暂无评论

Artificial gannet optimization enabled deep convolutional neural network for autism spectrum disorders classification using MRI image

引用

Multimedia Tools and Applications 2024年第30期83卷 74757-74783页

作者： Prasad, Vadamodula Ganeshan, R. Rajeswari, R. Department of Computer Science & amp Engineering Lendi Institute of Engineering & ampTechnology Jonnada Village Andhra Pradesh Vizianagaram District 535005 India School of Computing Science and Engineering VIT Bhopal University Kothrikalan Madhya Pradesh Sehore466114 India Department of Electronics and Communication Engineering Rajalakshmi Institute of Technology Chennai India

Autism Spectrum Disorder (ASD) is a neurodevelopment-based disability caused by variations in the brain. This may cause impact on social skills and communication of an individual. Autism is a highly challenging issue to diagnose at the early stages. ASD is one of the important problems to diagnose because it starts manifesting at low ages. This paper aims at ASD classification using MRI Images by Artificial Gannet Optimization enabled Deep Convolutional Neural Network (AGO_DCNN). Here, an MRI image is assumed that be subjected to pre-processing of the image and feature extraction phases as an input. The bilateral filter is employed to remove the noises from the input MRI image and in the pre-processing of an image stage Region of Interest (ROI) extraction is conducted. The pivotal region extraction phase receives a filtered image after which AGO is used to extract the pivotal region. AGO is a newly designed approach by merging two optimizations namely Artificial Ecosystem-based Optimization (AEO) and Gannet Optimization Algorithm (GOA). At the same time, features are extracted from the input image during the feature extraction stage. In a feature extraction stage, some features like texture and statistical features are extracted. At last, the classification of ASD is conducted using DCNN, wherein by AGO the classifier is tuned. Furthermore, AGO_DCNN attained better outcomes in terms of maximal True Positive Rate (TPR), True Negative Rate (TNR), and accuracy values of about 93.7%, 90.8%, 96.8% and False Positive Rate (FPR) and minimal False Negative Rate (FNR) and values of 78.7% and 74.7%. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

RealDriftGenerator: A Novel Approach to Generate Concept Drift in Real World Scenario

RealDriftGenerator: A Novel Approach to Generate Concept Dri...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Lin, Borong Huang, Chao Zhu, Xiaohui Jin, Nanlin School of Advance Technology Xi'an Jiaotong-Liverpool University Department of Computer Science and Software Engineering SuZhou China University of Liverpool Department of Computer Science Liverpool United Kingdom

ISBN: (纸本)9781665410205

Concept drift refers to the probability distribution of data generation changes over time in a data stream environment. In recent years, there has been an increasing interest in drift detection models. However, due to the lack of labeled concept drift datasets, most researchers tend to using synthetic drift data generators for model training. These generators only have relatively simple feature distributions, which fail to capture the complexity found in real-world scenarios. This paper introduces a real scenario concept drift label generator (RealDriftGenerator). This generator aims to preserve the complexity and temporal correlation of real-world scenario while generating concept drifts with user defined drift positions and drift widths. The validation result show that the temporal correlation coefficients of RealDriftGenerator is significantly higher than benchmark drift generators. Additionally, the ability of RealDriftGenerator to capture the complexity in real-world scenarios is 20% higher than benchmark drift generators(measured by model performance). The source code of RealDriftGenerator has been published on https://***/sniperrifle71/realDriftGenerator. © 2024 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Semantics Preserving Emoji Recommendation with Large Language Models

Semantics Preserving Emoji Recommendation with Large Languag...

引用

2024 IEEE International Conference on Big Data, BigData 2024

作者： Qiu, Zhongyi Qiu, Kangyi Lyu, Hanjia Xiong, Wei Luo, Jiebo Georgia Institute of Technology School of Computational Science and Engineering AtlantaGA United States Georgia Institute of Technology School of Computer Science AtlantaGA United States University of Rochester Department of Computer Science RochesterNY United States

ISBN: (纸本)9798350362480

Emojis have become an integral part of digital communication, enriching text by conveying emotions, tone, and intent. Existing emoji recommendation methods are primarily evaluated based on their ability to match the exact emoji a user chooses in the original text. However, they ignore the essence of users' behavior on social media in that each text can correspond to multiple reasonable emojis. To better assess a model's ability to align with such real-world emoji usage, we propose a new semantics preserving evaluation framework for emoji recommendation, which measures a model's ability to recommend emojis that maintain the semantic consistency with the user's text. To evaluate how well a model preserves semantics, we assess whether the predicted affective state, demographic profile, and attitudinal stance of the user remain unchanged. If these attributes are preserved, we consider the recommended emojis to have maintained the original semantics. The advanced abilities of Large Language Models (LLMs) in understanding and generating nuanced, contextually relevant output make them well-suited for handling the complexities of semantics preserving emoji recommendation. To this end, we construct a comprehensive benchmark to systematically assess the performance of six proprietary and open-source LLMs using different prompting techniques on our task. Our experiments demonstrate that GPT-4o outperforms other LLMs, achieving a semantics preservation score of 79.23%. Additionally, we conduct case studies to analyze model biases in downstream classification tasks and evaluate the diversity of the recommended emojis (https://***/VIStA-H/SemanticsPreservingEmojiRec). © 2024 IEEE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Caching Techniques in Edge Computing and Challenges 3

Caching Techniques in Edge Computing and Challenges

引用

3rd International Conference on Advancement in Electronics and Communication engineering, AECE 2023

作者： Kumar, Sumit Dash, Yajnaseni Galgotias University Department of Computer Science & Engineering Uttar Pradesh India School of Computer Science Engineering and Technology Bennett University Uttar Pradesh India

ISBN: (纸本)9798350330724

Edge computing, a distributed computing concept, brings data processing and storage closer to endpoints or edge devices. Caching methods are crucial in edge computing environments for optimizing performance and minimizing latency and enable faster response times, efficient bandwidth utilization, and enhanced scalability. Edge computing uses caching techniques strategically based on user behaviour studies and access patterns to boost scalability and reduce network congestion. Caching techniques increase the efficacy and performance of edge computing. The parameters that influence efficacy include cache management strategies, network conditions, application features, and data access patterns. This paper presents a brief overview of the caching technologies utilized in edge computing and their challenges. © 2023 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

A Robust Low-Rank Tensor Decomposition and Quantization based Compression Method 40

A Robust Low-Rank Tensor Decomposition and Quantization base...

引用

40th IEEE International Conference on Data engineering, ICDE 2024

作者： Ouyang, Yudian Xie, Kun Wen, Jigang Xie, Gaogang Li, Kenli College of Computer Science and Electronics Engineering Hunan University Changsha China Hangzhou Institute of Advanced Technology Hangzhou China School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan China Institute of Computer Network Information Center Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350317152

Tensor data is widely used in fields such as smart grids, cloud systems, and deep learning. As the scale of this data increases, storage and transmission costs rise significantly. Many tensor data exhibit low-rank structures, offering the potential for data compression through low-rank decomposition techniques. Tucker decomposition, a typical low-rank decomposition technique, achieves data compression and interpretability by capturing complex data correlations and representing the original tensor with a compact core tensor and factor matrices. However, the compression ratio provided by Tucker decomposition is often insufficient, particularly for large-scale tensors. To tackle this issue, we propose a robust low-rank tensor compression method that leverages Tucker decomposition with quantization and coding. Initially, we establish a robust Tucker decomposition framework that decomposes the low-rank tensor into a core tensor and factor matrices using well-designed Tucker rank-setting rules. This framework effectively handles noise and missing values. Subsequently, we conduct an in-depth analysis of the numerical characteristics of the core tensor and factor matrices within the Tucker decomposition framework. Based on their distinct characteristics, we design tailored quantization and coding schemes to compress the core tensor and factor matrices, respectively, thereby significantly improving the compression ratio of Tucker decomposition while maintaining high accu-racy. Through extensive experiments on four publicly available datasets (which can form 3 or 4 order tensors), we demonstrate that our approach can achieve compression ratios 4×-10× higher than the best competitor, with recovery errors improved by 8% -42%. © 2024 IEEE.

关键词： Tensors

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：