检索结果-内蒙古大学图书馆

Detecting and Preventing of Attacks in Cloud Computing Using Hybrid Algorithm

Intelligent Automation & Soft Computing 2023年第1期35卷 79-95页

作者： R.S.Aashmi T.Jaya Department of Computer Science and Engineering CSI Institute of TechnologyThovalaiIndia Department of Electronic Communications and Engineering CSI Institute of TechnologyThovalaiIndia

Cloud computing is the technology that is currently used to provide users with infrastructure,platform,and software services *** this system,Platform as a Service(PaaS)offers a medium headed for a web development platform that uniformly distributes the requests and *** using Denial of service(DoS)and Distributed Denial of Service(DDoS)attacks abruptly interrupt these *** though several existing methods like signature-based,statistical anomaly-based,and stateful protocol analysis are available,they are not sufficient enough to get rid of Denial of service(DoS)and Distributed Denial of Service(DDoS)attacks and hence there is a great need for a definite *** this issue,we propose an improved hybrid algorithm which is a combination of Multivariate correlation analysis,Spearman coefficient,and mitigation *** can easily differentiate common traffic and attack *** only that,it greatly helps the network to distribute the resources only for authenticated *** effects of comparing with the normalized information have shown an extra encouraging detection accuracy of 99%for the numerous DoS attack as well as DDoS attacks.

关键词： Hybrid algorithm(HA) distributed denial of service(DDoS) denial of service(DoS) platform as a service(PaaS) infrastructure as a service(IaaS) software as a service(SaaS)

来源：评论

学校读者我要写书评

暂无评论

Unmasking Disinformation: Detection of Fake News Online Using Learning Techniques 6

Unmasking Disinformation: Detection of Fake News Online Usin...

引用

6th IEEE International Conference on Emerging Smart Computing and informatics, ESCI 2024

作者： Shaikh, Numair Petkar, Pallavi Sonawane, Sheetal SCTR's Pune Institute of Computer Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350306613

In an era where fake news proliferates effortlessly across social media platforms, the task of discerning reliable news sources has become increasingly challenging. Detecting fake news in the realm of social media presents unique characteristics and complexities that render traditional detection algorithms ineffective. Recent research endeavors have sought to address these challenges by leveraging a diverse array of methods, including machine learning, deep learning, feature engineering and graph mining. In our research, we investigate the detection of fake news by employing a combination of traditional machine learning algorithms and deep learning models for fake news classification. Furthermore, we extend our research by conducting real-Time analysis for fake news detection using Twitter data and data from fact-checking sites. By combining the strengths of traditional machine learning and deep learning, our research offers a holistic approach to fake news detection, enhancing the accuracy and robustness of our results. © 2024 IEEE.

关键词： Fake News Detection Natural Language Processing Text Classification

来源：评论

学校读者我要写书评

暂无评论

A Fully Homomorphic Encryption based approach for Privacy Preserved Pre-processing of MedicalTranscripts 15

A Fully Homomorphic Encryption based approach for Privacy Pr...

引用

15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Gaikwad, Vijayendra S. Patil, Aditya Panditrao, Ruturaj Pareek, Tanisha Agrawal, Muskan Department of Computer Engineering SCTR's Pune Institute of Computer Technology Pune India

ISBN: (纸本)9798331300579

Natural Language Processing holds immense potential for extracting insights from healthcare data, but it demands stringent privacy ***-preserving NLP techniques, notably Fully Homomorphic Encryption (FHE), offer a path to advanced analytics while preserving patient data *** paper marks the culmination of our initial phase, focusing on data preparation and ***'ve employed FHE with the CKKS scheme to ensure data remains *** evaluation adapts multiclass classification metrics, addressing the distinct nature of healthcare *** we conclude this phase, we emphasize that this is only the *** steps will focus on developing NLP models trained on encrypted *** work highlights the intersection of data privacy and advanced analytics in healthcare, ultimately benefiting healthcare providers and patients. © Grenze Scientific Society, 2024.

关键词： Differential privacy

来源：评论

学校读者我要写书评

暂无评论

Security to text (S2T): multi-layered based security approaches for secret text content

引用

Multimedia Tools and Applications 2025年第15期84卷 15151-15171页

作者： Kashid, Shamal Awasthi, Lalit K. Berwal, Krishan Department of Computer Science and Engineering National Institute of Technology Uttarakhand IN Srinagar India Faculty of Communication Engineering Military College of Telecommunication Engineering IN Mhow India

In the digital world, text data is produced in an unstructured manner across various communication channels. Extracting valuable information from such data with security is crucial and requires the development of techniques in text mining, information retrieval, and natural language processing (NLP). To solve this issue, we introduce two novel approaches: keyword extraction (KE) and a multi-layered secret sharing scheme (MLSS) to provide security to extracted keywords rather than overall text documents. The KE approach encompasses a sequence of text pre-processing procedures, including tokenization, stopword removal, stemming, and bag of words representation, followed by indexing. This methodology aims to efficiently extract keywords from text datasets. For this research work, we have proposed three datasets, including text messages, whatsapp messages, and electronic mail. MLSS enhances the security of extracted textual data by leveraging text pre-processing steps. This scheme ensures better confidentiality and the non-revealment of sensitive information. Additionally, we evaluate our KE model on our dataset as well as on standard datasets. Experimental results demonstrate the effectiveness of our proposed security to text (S2T) model, which outperform existing state-of-the-art approaches. The model obtains a 100% correlation between the reconstructed text and the original text. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Extraction

来源：评论

学校读者我要写书评

暂无评论

Multimodal Integration, Fine Tuning of Large Language Model for Autism Support 5

Multimodal Integration, Fine Tuning of Large Language Model ...

引用

5th International Conference on Mobile Computing and Sustainable informatics, ICMCSI 2024

作者： Pai, Krishna Jagwani, Vidhita Pandita, Shivalik Kalbande, Dhananjay Sardar Patel Institute of Technology Department of Computer Engineering Mumbai India Sardar Patel Institute of Technology Department of Computer Science and Engineering Mumbai India

ISBN: (纸本)9798350395235

This research project centres on creating an inclusive environment for the specially-abled. Created an app that integrates real-time object detection and speech-to-text capabilities which provides a multi-modal user experience with the pre-trained Model. Incorporated parameter-efficient fine-tuning using Low-Rank Adaptation (LoRA) to emulate the behaviour of an autism *** second module of the research employs YOLOv5 and machine learning to analyze therapy videos to get interaction timestamps and statistical insights. It automates the identification of interactions and serves as a valuable aid to guardians and *** paper details the methodology for real-time object detection using YOLO, SSD Mobilenet and enhances understanding in the context of adaptation of Language Models for a particular use case. Furthermore, dives deeper into the intricacies of interaction monitoring using bounding boxes in YOLO. By pushing the boundaries of Large Language Model capabilities, this research not only refines language models but also lays the foundation for their application in dynamic contexts of the real world, exemplifying their revolutionary potential. © 2024 IEEE.

关键词： Image recognition

来源：评论

学校读者我要写书评

暂无评论

Review and analysis for state-of-the-art NLP models

引用

International Journal of Systems, Control and Communications 2023年第1期15卷 48-78页

作者： Dikshit, Subrit Dixit, Rahul Shukla, Abhiram Department of Computer Science and Engineering Indian Institute of Information Technology Pune India Department of Civil Engineering Indian Institute of Technology Kanpur India

Natural language processing (NLP) is an area of research and study that makes it possible for computers to comprehend human language by utilising software engineering concepts from computer science and artificial intelligence. This work presents seven classifications and 21 state-of-the-art models with a survey of the operating principles. We also provide a comparative study of all models based on metrics such as accuracy, F1 score, exact match, squad scores, glue and superglue dataset scores. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Explicable knowledge graph (X-KG): generating knowledge graphs for explainable artificial intelligence and querying them by translating natural language queries to SPARQL

引用

International Journal of Information technology (Singapore) 2024年第3期16卷 1605-1615页

作者： Shaikh, Numair Chauhan, Tavishee Patil, Jayesh Sonawane, Sheetal Department of Computer Engineering SCTR’s Pune Institute of Computer Technology Maharashtra Dhankawdi Pune 411043 India

Knowledge graphs represent a potent instrument for the classification and exhibition of data, as they encompass a systematic approach for the containment and retrieval of multifarious datasets. In finance, the utilization of knowledge graphs for the organization of company-oriented data constitutes an invaluable source of insights, thus enabling informed decision-making. In a parallel, knowledge graph systems centered on COVID-19 within the healthcare sphere may assist medical professionals in the making of resolute choices. These applications highlight knowledge graphs’ ability to revolutionize decision-making procedures by providing a comprehensive comprehension of the given subject. To tackle this, we propose a solution that begets and implements knowledge graphs in two separate domains: finance and healthcare. To ensure the creation of explicable AI systems and improve the accessibility of information within these knowledge graphs, we introduce the conversion of natural language queries into SPARQL queries. By fine-tuning our model, we illustrate the system’s superior performance. Furthermore, we appraise the adequacy of the constructed knowledge graphs and contrast them with widely employed alternatives. Our work accentuates the adaptability of the proposed solution, as it can operate seamlessly with diverse datasets requiring minimal modifications. © 2024, The Author(s), under exclusive licence to Bharati Vidyapeeth's institute of computer Applications and Management.

关键词： Explainable artificial intelligence Knowledge graphs Natural language processing Q& A systems Query translation

来源：评论

学校读者我要写书评

暂无评论

Integration of cloud-based scheme with industrial wireless sensor network for data publishing in privacy of point source

引用

International Journal of Cloud Computing 2024年第2期13卷 124-138页

作者： Ravindhar, N.V. Sasikumar, S. Bharathiraja, N. Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamil Nadu India Department of Computer Science and Engineering Saveetha Engineering College Tamil Nadu India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

Wireless sensor networks (WSNs) are normally conveyed in arbitrary regions with no security. The source area uncovers significant data about targets. In this paper, a plan dependent on the cloud utilising data publishing in privacy of point source is proposed to resolve the issue of source area security. Then, at that point, a cloud-moulded phony area of interest is made to add counterfeit parcels into the WSN to confound the enemy and give a far-reaching protection area. Every important parcel is steered through a way that is very hard for the area of interest finding enemy to discover straightforwardly. Recreation results represent that the plan can forestall antagonistic catch and keep a significant degree of security insurance simultaneously. The energy utilisation in this plan applies restricted impact on the organisation lifetime contrasted and a cloud-based plan and an all-course irregular steering calculation conspire. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Wireless sensor networks

来源：评论

学校读者我要写书评

暂无评论

A Hybrid IoT and Machine Learning Approach for Crop Recommendation Using a Voting Ensemble Model 2

A Hybrid IoT and Machine Learning Approach for Crop Recommen...

引用

2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Suresh, A. Geetha Vani, B. Lavanya, M. Kumar, R.G. Siddharth Institute of Engineering & Technology Department of Computer Science and Engineering A.P India

ISBN: (纸本)9798350317558

Agriculture is a key component of a nation's economy. In the traditional method, farmers rely on experience to determine the ideal climate and environment for a given crop. technology is advancing, and while the system depends on it to some extent, improvements are still required. This study presents an Internet of Things (IoT) based crop recommendation system that uses Machine learning (ML) to use the value that IoT devices collect from the soil. Initially, we utilized baseline ML classifier models like Support vector machine (SVM), K-Nearest Neighbor(KNN), Random forest (RF), and Random forest (NB).Then we employed an ensemble model to detect the suitable crops. We employed several IoT sensors in our research. The DHT11 sensor collects real-time environmental data, such as temperature and humidity. During crop recording, vital soil parameters like potassium and phosphorus - which are essential for crop growth - are measured using an NPK sensor, a pH sensor, and a rain sensor. These sensors can be seamlessly integrated by the IoT device, offering an effective way to collect crucial agricultural data. The Voting Base Ensemble performs exceptionally well in terms of precision, recall, and F1 score measures. The voting Base Ensemble algorithm improves metrics such as F-score, recall, and precision by up to 98%. A thorough evaluation of soil conditions is made possible by the integration of various sensors, and the application of an ensemble model enables accurate crop recommendations based on environmental factors. © 2024 IEEE.

关键词： Agriculture Crop Recommendation Ensemble IoT Machine Learning

来源：评论

学校读者我要写书评

暂无评论

Behavioral insights into compression: a study of Move-to-Front-or-Middle deterministic online algorithm through sequence classification and characterization

引用

International Journal of Information technology (Singapore) 2025年第1期17卷 189-203页

作者： Baisakh Mohapatra, Hitesh Guru, Abhishek Department of Computer Science and Engineering Sambalpur University Institute of Information Technology Sambalpur India Computer Science and Engineering GMR Institute of Technology Andhra Pradesh Rajam India School of Computer Engineering KIIT Deemed to Be University Bhubanseswar India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram India

Since the list update problem was applied to data compression as an effective encoding technique, numerous deterministic algorithms have been studied and analyzed. A powerful strategy, Move-to-Front (MTF), involves moving an accessed item to the front of the list immediately. Theoretical analysis has demonstrated MTF’s potential, showing it to be 2-competitive through competitive analysis. This success has inspired researchers to develop various intriguing MTF variants and assess their performance both theoretically and experimentally. One such variant, Move-to-Front-or-Middle (MFM), has been experimentally shown that MFM performed better than the classic MTF on Calgary and Cantebury Datasets. However, the experimental performance alone does not provide sufficient insight into the internal behavior of the algorithm or explain why its performance surpasses MTF on certain datasets. Therefore, in this paper, we conduct a detailed behavioral study of MFM through sequence classification and characterization to gain deeper understanding of the algorithm and aims to reconcile the disparity between theoretical and experimental outcomes. This paper also by classifying and characterizing MFM’s performance across various request sequences, considering both the presence and absence of locality of reference. © Bharati Vidyapeeth's institute of computer Applications and Management 2024.

关键词： Competitive analysis Deterministic list update algorithm List update problem Sequence classification

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：