检索结果-内蒙古大学图书馆

Achieving Secured Medical Network (SMN) through Stateless Mechanism and SkeyM in Medical-Internet of Things (M-IoT)

Journal of engineering and Applied Science 2024年第1期71卷 1-22页

作者： Nithya, S. Palanisamy, SatheeshKumar Nivethitha, T. Department of Computer Science and Engineering Kumaraguru College of Technology Tamil Nadu Coimbatore641049 India Department of Electronics and Communication Engineering BMS Institute of Technology and Management Karnataka Bengaluru560064 India Department of Electronics and Communication Engineering Sri Eshwar College of Engineering Tamil Nadu Coimbatore641202 India

Medical Internet of Things (M-IoT) synchronizes medical devices in a network to provide smart healthcare monitoring to doctors and to provide an interactive model for patients. This embedded networked system gained lots of importance in the last few years. Now almost every hospital adopts M-IoT. Though it had a lot of challenges in the initial stages of implementation such as feasibility, accuracy, and autonomy, now it has bridged the flaws with the help of several researchers in this field. But still, M-IoT lags behind in security and privacy aspects due to which attackers can intrude on the network and exploit patients’ health data. By examining the various intensive security threats imposed on M-IoT a unique way of handling and transferring data over the network is proposed in this paper. From our research findings, this would resolve the data security issues in M-IoT and commence the next advancements. © The Author(s) 2024.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

An Efficient Approach to Resolve Social Dilemma in P2P Networks 37th

An Efficient Approach to Resolve Social Dilemma in P2P Net...

引用

37th International Conference on Advanced Information Networking and Applications, AINA 2023

作者： Kishor, Avadh Niyogi, Rajdeep Department of Computer Science and Engineering ABV-Indian Institute of Information Technology and Management Gwalior Gwalior India Department of Computer Science and Engineering Indian Institute of Technology Roorkee Roorkee India

ISBN: (纸本)9783031290558

The premise of a peer-to-peer (P2P) system is based on the voluntary contribution of peers. However, an inherent conflict between individual rationality and social welfare engenders a new situation called the free-rider problem, in which some peers consume the resource without contributing to return. The tendency of free-riding in a P2P system is a critical issue, as it threatens the viability of the whole system. This can be reduced by employing an effective mechanism that deters the free-riding by incentivizing peers to contribute to the system. In this paper, we consider a social planner that acts as a decision-maker among individual agents. We cast the problem as a constrained optimization problem. A metaheuristic algorithm called the artificial bee colony algorithm is used to solve the problem. The empirical results show that each peer contributes to its full capacity and receives a fair (equal) profit share. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Securing the Cyber Supply Chain: A Risk-based Approach to Threat Assessment and Mitigation 4

Securing the Cyber Supply Chain: A Risk-based Approach to Th...

引用

4th International Conference on Electronics and Sustainable Communication Systems, ICESC 2023

作者： Phani Prathyusha, J.R.V.S.L.P. Esther Jyothi, V. Jhansi, Vadlamudi Sampreeth Chowdary, N. Madhuri, A. Sindhura, S. Velagapudi Ramakrishna Siddhartha Engineering College Department of Computer Applications Vijayawada India P.V.P. Siddhartha Institute of Technology Department of Computer Science and Engineering Vijayawada India Nri Institute of Technology Department of Computer Science and Engineering Agiripalli India

ISBN: (纸本)9798350300093

The system of Cyber Supply Chain (CSC) is characterized by its complexity, consisting of several subsystems, each responsible for a distinct set of responsibilities. Securing the supply chain presents a challenge due to the presence of vulnerabilities and threats throughout the system that has the potential to be taken advantage of at any time, considering that any component of the system is susceptible to such attacks. As a result, supply chain security is difficult to achieve. This has the potential to create a significant interruption to the overall continuity of the company. Therefore, it is of the utmost importance to identify the hazards and make educated guesses about their likely outcomes so that organizations can take the appropriate precautions to ensure the safety of their supply chains. By leveraging a range of factors, such as the expertise and incentives of threat actors, Tactics, Techniques, and Procedures (TT and P), as well as Indicators of Compromise (IoC), the analysis of Cyber Threat Intelligence (CTI) offers valuable information on both identified ansignd unidentified cybersecurity threats. In order to increase the safety of the cyber supply chain, the purpose of this article is to investigate and speculate on potential dangers. The CTI and Machine Learning (ML) approaches have been employed by us in order to study and forecast the risks based on the CTI attributes. This makes it possible to detect the inherent CSC vulnerabilities, which enables suitable control. To enhance the overall security of computer systems, it is imperative to implement specific actions, including the collection of CTI data and the adoption of various machine learning techniques. These techniques encompass Logistic Regression (LG), Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), Cat Boost, and Gradient Boost, which are employed in analyzing the Microsoft Malware Prediction dataset to create predictive analytics. This is done in order to illustrate t

关键词： Supply chains

来源：评论

学校读者我要写书评

暂无评论

Interactive Learning Environment for Networking Topics based on Augmented Reality

Interactive Learning Environment for Networking Topics based...

引用

International Conference on computer Vision and Internet of Things 2023, ICCVIoT 2023

作者： Kanimozhi, S. Sairamesh, L. School of Computer Science and Engineering Vellore Institute of Technology Chennai India Department of Computer Science and Engineering St. Joseph's Institute of Technology Chennai India

ISBN: (纸本)9781839539848

Augmented Reality (AR) implemented on mobile devices has emerged as a prominent subject of study within the field of mobile applications and human-machine interaction. The mobile augmented reality (AR) technique integrates intelligent display, registration tracking, virtual and reality convergence, and human-computer interactions using portable devices or intelligent terminals. This enables the seamless integration of the 3D virtual object with the customer's real-life environment, thereby enhancing the perceived depth and breadth of the experience. Augmented reality has been extensively utilized across diverse domains, including the field of education. In the domain of education, augmented reality is employed to enhance the level of engagement and appeal in the learning process. Beginning with the issue of acquiring knowledge about computer networks, it is observed that the conventional approach involves the introduction of network devices, TCP/IP models, and OSI models. This research addresses the problem by creating a learning media solution that utilizes augmented reality (AR) technology. AR technology integrates two-dimensional or three-dimensional virtual objects into a real environment and displays these virtual objects in real-time. The novelty of this work implies on the design of augmented reality (AR) applications for teaching the OSI model in the field of computer networks. The aim is to enhance comprehension, stimulate motivation, and generate student interest in learning. © The Institution of engineering & technology 2023.

关键词： Augmented reality

来源：评论

学校读者我要写书评

暂无评论

A Paradigm Shift in Ethereum Network Analysis Through Google BigQuery,Portation, and Visualization 6

A Paradigm Shift in Ethereum Network Analysis Through Google...

引用

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

作者： Suresh Kumar, N. Mirdula, S. Singh, Pushpa Gayathri, T. Jayanthi, S. Anandraj, M. School of Computer Science and Engineering Jain Deemed-to-be University Ramanagara India SRM TRP Engineering College Department of Electronic and Communication Engineering Trichy India IILM University Department of Computer Science and Engineering Greater Noida India MVJ College of Engineering Department of Computer Science and Engineering Bangalore India Guru Nanak Institute of Technology Department of Information Technology Ibrahimpatnam India Mahendra College of Engineering Department of Computer Science and Engineering Salem India

ISBN: (纸本)9798350306613

The primary objective of this research is to comprehensively explore and analyze the dynamics of the Ethereum network using innovative methodologies and system architectures. The study aims to extract meaningful statistics from the Ethereum blockchain, focusing on account activity, popularity trends, and the distribution of transactions. Through rigorous data collection, robust query construction, and advanced analytical techniques, the research seeks to provide valuable insights into how the Ethereum network has evolved, particularly in the aftermath of the 'crypto bubble explosion.' The overarching goal is to contribute to the understanding of Ethereum's structural patterns, user behaviors, and the impact of external factors on the network. The research has yielded significant results, unveiling key insights into Ethereum network dynamics. The data collection phase, facilitated by Google BigQuery, successfully captured and filtered relevant information from a specific block range post the 'crypto bubble explosion.' The SQL queries, strategically designed for active account identification and popularity assessment, demonstrated efficiency and accuracy in handling the vast Ethereum dataset. The proposed system, introducing the novel methodology of 'portation,' showcased its efficiency in extracting and interpreting Ethereum blockchain data using Google BigQuery. The system architecture, as illustrated in the diagram, proved to be a well-coordinated and dynamic framework, emphasizing the seamless flow of data and processes. © 2024 IEEE.

关键词： Crypto Bubble Explosion Decentralized Data Transactions Ethereum Blockchain Google BigQuery Power-law Analysis

来源：评论

学校读者我要写书评

暂无评论

Stress Analysis Prediction for Coma Patient Using Machine Learning 5th

Stress Analysis Prediction for Coma Patient Using Machine Le...

引用

5th International Conference on Data and Information Sciences, ICDIS 2023

作者： Alwin Infant, P. Charulatha, J. Sadhana, G. Ragavendra, K. Computer Science and Engineering Panimalar Engineering College Chennai India Department of Information Technology Hindustan Institute of Technology and Science Chennai India

ISBN: (纸本)9789819969050

Today’s working IT professionals frequently struggle with stress issues. The patient is now more likely to experience stress due to changing lifestyle and workplace cultures. Even while many companies and sectors deliver welfare programs and also make efforts to enhance work environments, the issue remains off from grasp. In this paper, we will utilize various techniques to analyze the stress patterns of working people and identify the variables that exert a massive effect on the system's distress. By utilizing machine learning techniques to forecast models to predict the threats of stressor encountered prognosis through using machine learning, we hope to streamline this procedure. In the working class, mental health illnesses linked to stress are not unusual. Concerns about the same have previously been highlighted by several researchers. In order to do this, information from coma patient answers from working medical experts’ mental health data was taken into consideration. After data extraction and preprocessing, various machine learning approaches were employed to supervise our framework. In this case, the mechanism can apply the machine learning techniques such as decision tree, random forest, KNN, logistic regression, and Naive Bayes. Results of the experiments demonstrated the system’s improved performance. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

A Secure and Efficient Biometric Template Protection Scheme for Palmprint Recognition System

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2023年第5期4卷 1051-1063页

作者： Sardar, Alamgir Umer, Saiyed Rout, Ranjeet Kumar Khan, Muhammad Khurram Aliah University Department of Computer Science and Engineering Kolkata700156 India National Institute of Technology Department of Computer Science and Engineering Srinagar190006 India King Saud University Center of Excellence in Information Assurance Riyadh11451 Saudi Arabia

The accuracy and security of a biometric system are the two sides of a coin. A biometric system must be simple, flexible, efficient, and secure enough from unauthorized access. Concerning these requirements, this article presents an enhanced palmprint recognition system with superior performance and improved biometric template protection schemes. This method comprises five components: image preprocessing, feature extraction, cancelable biometrics, classification, and Bio-Cryptosystem. The palm texture region is extracted from the input hand image during preprocessing. A feature representation technique is then used to extract discriminant features from the palmprint texture patterns. The extracted features are then analyzed using an information coding scheme to compute a user-specific token. Here, the user-specific tokens along with the original palmprint features are used to calculate the feature vectors for the cancelable biometric system. A novel Bio-Cryptosystem has been proposed to protect templates with high security where there is no need to remember the users' tokens. Cancelable feature vectors are kept online in encrypted form using the proposed Bio-Cryptosystem, which is used to identify or verify the subjects after decryption. The original feature vectors are kept offline to prevent these from external attacks and misuse. Finally, the multiclass linear support vector machine has been used for user classification. For experimental purposes, two benchmark hand image databases: BOSPHORUS and CASIA-Palmprint, are employed, and the proposed system has achieved nearly 100% correct recognition rate in cancelable domain for both the employed databases. Finally, the performance comparison in terms of both verification and identification for the palmprint and the cancelable palmprint recognition systems with the existing state-of-the-art methods shows the superiority of the proposed system. © 2020 IEEE.

关键词： Palmprint recognition

来源：评论

学校读者我要写书评

暂无评论

Job Resumes Recommendation using Integration of Fuzzy Discernibility Matrix Feature Selection and Convolutional Neural Network Multi-label Text Classification

Informatica (Slovenia)

引用

Informatica (Slovenia) 2025年第13期49卷 49-58页

作者： Hayami, Regiolina Yusoff, Nooraini Daud, Kauthar Mohd Fatma, Yulia Department of Informatics Engineering Faculty Computer Science Universitas Muhammadiyah Riau Indonesia Faculty of Data Science and Computing Universiti Malaysia Kelantan 16100 Malaysia Center for Artificial Intelligence Technology Faculty of Information Science and Technology Universiti Kebangsaan Malaysia 43600 Malaysia

The manual analysis of job resumes poses specific challenges, including the time-intensive process and the high likelihood of human error, emphasizing the need for automation in content-based recommendations. Recent advancements in deep learning, particularly Convolutional Neural Networks (CNN) for Multi-label Text Classification (MLTC), offer a promising solution for addressing these challenges through artificial intelligence. While CNN is renowned for its robust feature extraction capabilities, it faces specific challenges such as managing high-dimensional data and poor data interpretability. To address these limitations, this study employs the Fuzzy Discernibility Matrix (FDM) feature selection technique to determine the relevance of skills for each job vacancy. FDM assigns weights to the features of each job category and ranks their relevance based on the highest scores, which are then utilized in the MLTC CNN model. The integration of FDM and MLTC CNN serves as the foundation for generating content-based recommendations derived from key features in job resumes. This study produces a content-based job recommendation system that displays the top three job categories, accompanied by explanations of the skills supporting each selected category. These recommendations also consider cosine similarity values between analyzed items and the integrated results of FDM and MLTC CNN. The application of FDM for feature weighting has been proven to enhance multi-label text classification outcomes by providing better insights during the feature selection process. With a recall of 97.26%, precision of 94.81%, and accuracy of 98.58%, the MLTC model integrating FDM feature selection and CNN demonstrates robust performance characteristics in content-based job recommendation tasks. © 2025 Slovene Society Informatika. All rights reserved.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Anomaly Detection in Social Media Texts Using Optimal Convolutional Neural Network

引用

Intelligent Automation & Soft Computing 2023年第4期36卷 1027-1042页

作者： Swarna Sudha Muppudathi Valarmathi Krishnasamy Department of Computer Science and Engineering Ramco Institute of TechnologyRajapalayam626117India Department of Electronics and Communication Engineering P.S.R.Engineering CollegeSivakasi626140India

Social Networking Sites(SNSs)are nowadays utilized by the whole world to share ideas,images,and valuable contents by means of a post to reach a group of *** use of SNS often inﬂicts the physical and the mental health of the ***,researchers often focus on identifying the illegal beha-viors in the SNS to reduce its negative inﬂ*** state-of-art Natural Language processing techniques for anomaly detection have utilized a wide anno-tated corpus to identify the anomalies and they are often time-consuming as well as certainly do not guarantee maximum *** overcome these issues,the proposed methodology utilizes a Modiﬁed Convolutional Neural Network(MCNN)using stochastic pooling and a Leaky Rectiﬁed Linear Unit(LReLU).Here,each word in the social media text is analyzed based on its *** stochastic pooling accurately detects the anomalous social media posts and reduces the chance of overﬁ*** LReLU overcomes the high computational cost and gradient vanishing problem associated with other activation *** also doesn’t stop the learning process when the values are *** MCNN computes a speciﬁed score value using a novel integrated anomaly detection *** on the score value,the anomalies are identiﬁed.A Teaching Learn-ing based Optimization(TLBO)algorithm has been used to optimize the feature extraction phase of the modiﬁed CNN and fast convergence is *** this way,the performance of the model is enhanced in terms of classiﬁcation *** efﬁciency of the proposed technique is compared with the state-of-art techni-ques in terms of accuracy,sensitivity,speciﬁcity,recall,and *** proposed MCNN-TLBO technique has provided an overall architecture of 97.85%,95.45%,and 97.55%for the three social media datasets namely Facebook,Twitter,and Reddit respectively.

关键词： Anomaly detection convolutional neural network social networking sites stochastic pooling teacher learner-based optimization

来源：评论

学校读者我要写书评

暂无评论

Fog Computing in IoT: Architecture and Applications 9

Fog Computing in IoT: Architecture and Applications

引用

9th International Conference on Science, technology, engineering and Mathematics, ICONSTEM 2024

作者： Agrawal, Anurag Vijay Shashi Gowridurga, A. Suresh Balakrishnan, T. Shaikh, Anwar Ahamed Kalaipriya, V. J. P. Institute of Engineering And Technology Department of Electronics And Communication Engineering Uttar Pradesh Meerut250001 India Ccs University Department of Computer Application Meerut250004 India Velammal Institute of Technology Department of Computer Science And Engineering Tamil Nadu 601204 India Saveetha School of Engineering Saveetha Institute of Medical And Technical Sciences Department of Computer Science And Engineering Tamil Nadu Thandalam602105 India KoneruLakshmaiah Education Foundation Department of Computer Science And Engineering Andhra Pradesh Vaddeswaram522502 India Rmk College of Engineering And Technology Department of Computer Science And Engineering Tamil Nadu Puduvoyal601206 India

ISBN: (纸本)9798350365092

This exploration paper explores the paradigm of Fog Computing as a transformative armature in the Internet of effects(IoT) geography. Fog Computing represents a decentralized approach, positioning computing coffers closer to the edge of the network, thereby addressing quiescence, bandwidth, and data sequestration challenges current in traditional polycentric IoT infrastructures. The paper provides an in-depth analysis of Fog Computing's armature, expounding its crucial factors similar to fog bumps, middleware, and edge bias. likewise, it investigates the different operations of Fog Computing in IoT, ranging from realtime data analytics, effective resource operation, to enhanced security and sequestration measures. By bridging the gap between edge bias and centralised pall waiters, Fog Computing emerges as a vital result, fostering the elaboration of scalable, effective, and responsive IoT ecosystems. This exploration contributes precious perceptivity to the architectural nuances and practical operations, paving the way for the integration of Fog Computing as a foundation in the ever-expanding realm of IoT technologies. © 2024 IEEE.

关键词： Fog computing

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：