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2nd IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Ou, Wenjisi Zheng, Wei Zhou, Qiang Jiangxi Vocational and Technical College of Information Application Department of Computer Technology Nanchang330043 China

ISBN: (纸本)9798350347456

The establishment of a network environment under the network environment under the network environment of the network environment. First of all, in view of the periodic characteristics of business requirements in the PaaS software system, the business cycle characteristics of the business system and the business cycle characteristics of the business system are integrated based on the business cycle characteristics of the business, and the business model of the business system is formed. The multi-objective optimization method based on multi-objective optimization is used to solve the multi-objective optimization problem. This paper proposes a Paas-oriented master-slave service model, and develops and applies it. Experiments show that if a finite resource is used in the whole system, then the whole system is limited, this method can maximize the utilization of resources in the system. This paper presents a new security threat assessment method based on cloud computing environment, and it has strong recognition. © 2023 IEEE.

关键词： Multiobjective optimization

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Selection of Digital Watermarking Techniques for Medical Image Security by Using the Fuzzy Analytical Hierarchy Process

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Recent Advances in computer Science and Communications 2023年第7期16卷 74-80页

作者： Ahmad, Masood Nadeem, Mohd Islam, Mohd Ali, Saquib Agrawal, Alka Khan, Raees Ahmad Department of Information Technology Babasaheb Bhimrao Ambedkar University Uttar Pradesh Lucknow226025 India Department of Computer Science & Application Era University Lucknow India

Background: The watermarking technique is a security algorithm for medical images and the patient's information. Watermarking is used for maintaining the robustness, integrity, confidentiality, authentication, and complexity of medical images. Objective: The selection of medical image watermarking technique is multi-criteria decision-making and an automatic way of algorithm selection for security and privacy. However, it is diffi-cult to select a better watermarking technique through traditional selection techniques. Methods: To deal with this problem, a multicriteria-based fuzzy analytic hierarchy process (FAHP) was proposed. This method is applied for algorithm selection for the security of medical images in healthcare. In this method, we first determined the list of criteria and alternatives, which directly affect the decision of the medical image security algorithm. Then, the proposed method was applied to the criteria and alternatives. Results: We provided the rank according to the obtained weights of the algorithm. Furthermore, the overall results and ranking of the algorithms were also presented in this article. Conclusion: Integrity was found to have the highest weight (0.509) compared to the other crite-ria. The weight of the other criteria, namely authentication, was 0.165, robustness was 0.151, con-fidentiality was 0.135, and complexity was 0.038. Thus, in terms of ranking, integrity was report-ed to be of the highest priority among the five criteria attributes. © 2023 Bentham Science Publishers.

关键词： Authentication

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An Overview of Clustering Algorithms for Credit Card Fraud Detection

An Overview of Clustering Algorithms for Credit Card Fraud D...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Jebaraj, N.R. Solomon Shekhawat, Jyoti Gupta, Rupal Department of Computer Science and Information Technology Bangalore India Computer Science & Application Vivekananda Global University Jaipur India Teetthanker Mahaveer University Department of Computing Sciences and Information Technology Uttar Pradesh Moradabad India

ISBN: (纸本)9798350383348

This paper offers a top-stage view of clustering algorithms that can be used for Clustering algorithms, which are robust and bendy techniques for uncovering patterns and anomalies in large datasets. Those algorithms can be used for grouping transactions with capabilities together with place, hour, gadgets bought, card holder, or each different characteristic related to the marketing. For credit card fraud detection, clustering algorithms are famous answers due to their capability to discover anomalous clusters that could represent fraudulent transactions. High-quality, well-known clustering algorithms and ok-way, hierarchical, and fuzzy clustering are mentioned as their particular packages. The paper also offers a few case studies concerning the usage of clustering algorithms for credit card fraud detection. This case research suggests real-global examples of how clustering algorithms may be implemented for credit rating card information. In the end, the paper outlines the demanding situations and possibilities of clustering algorithms. It is essential for banking structures, as unauthorized use of credit scorecards results in widespread economic losses. Detection of fraud is often predicated on gadgets mastering algorithms in conjunction with clustering algorithms. Clustering algorithms are the unsupervised getting-to-know method used to group patterns of facts based on similarity to find ability fraud. Famous clustering algorithms embody okay-manner, Gaussian aggregate models, and Self-Organizing Maps. Those algorithms are trying to differentiate legitimate clients from those committing fraud by figuring out clusters of ordinary behavior. Ok-manner uses an iterative manner to group data in keeping with Euclidean distance measures. Gaussian aggregate models use a probabilistic method to classify kinds of records and may incorporate preceding information approximately the statistics location if you want to generate extra accurate clusters. Self-organizing maps use a

关键词： aggregate detection Exceptional fraudulent functions

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Internet of Everything: A Review on Smart Healthcare Taxonomy, Research Challenges and Methodologies 14

Internet of Everything: A Review on Smart Healthcare Taxonom...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Raj, Anu Prakash, Shiva Srivastava, Jyoti Madan Mohan Malaviya University of Technolgy Information Technology & Computer Application Department Gorakhpur India

ISBN: (纸本)9798350335095

The Internet of Everything (IoE) has the potential to revolutionize many aspects of our daily lives, including healthcare, business and industrial world etc. Smart healthcare systems that utilize IoE technologies could greatly improve patient outcomes, increase efficiency, and reduce costs. However, there are several challenges that must be overcome in order to develop effective and reliable power supply systems for IoE-enabled healthcare devices. IoE healthcare devices may be deployed in a variety of settings, and the power supply system must be able to monitor and manage these devices remotely. The development of high-performance smart healthcare systems for the IoE requires the development of reliable and scalable power supply systems that can overcome the challenges of distribution, connection, charging technologies, and management. This paper mainly emphasizes on the IoE and their components that are used in the smart healthcare system and rising of the research challenges. In this paper, by addressing the taxonomy of healthcare and research challenges, researchers and businesses can develop innovative solutions that will transform healthcare delivery and improve patient outcomes. © 2023 IEEE.

关键词： Internet of Everything

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Research on Cloud Computing Security technology under computer Big Data Network 3

Research on Cloud Computing Security Technology under Comput...

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3rd IEEE International Conference on Electronic technology, Communication and information, ICETCI 2023

作者： Zhou, Qiang Ou, Wenjisi Zheng, Wei Jiangxi Vocational and Technical College of Information Application Department of Computer Technology Nanchang330043 China

ISBN: (纸本)9798350398410

In this paper, a parameter estimation-based security access integration method for computer network smart data is designed. The scale of data clustering is determined according to the distribution and evolution characteristics in the clustering process. Finally, this paper proposes a new security access control scheme. The system uses local abnormal factors to judge non-safe data and eliminates abnormal data according to the judgment results. The system sorts and outputs the factors that may have abnormal data points in the current time window. The Java object-oriented programming language is used. The network attack will be divided into fuzzy measures of DoS attack and non-DoS attack, and finally, the results of various attacks will be displayed. Simulation results show that this paper's entire access control scheme is highly feasible. The proposed algorithm has a high recognition rate. © 2023 IEEE.

关键词： Access control

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Investigating the Use of Spatial Transformer Networks and Recurrent Neural Networks for Medical Image Segmentation

Investigating the Use of Spatial Transformer Networks and Re...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Saxena, Vineet Nachappa, M.N. Shree, Ritu Teetthanker Mahaveer University Department of Computing Sciences and Information Technology Uttar Pradesh Moradabad India Department of Computer Science and Information Technology Bangalore India Computer Science & Application Vivekananda Global University Jaipur India

ISBN: (纸本)9798350383348

This paper investigates using popular deep learning models, Spatial Transformer Networks (STNs), and Recurrent Neural Networks (RNNs) for clinical picture segmentation. STNs are used to study a learnable pose-invariant body that permits image segmentation throughout exceptional segmentation tasks and affected person populace. RNNs seize temporal context within the facts and enhance segmentation accuracy. The paper evaluates the overall performance of the two models on the publicly available MIMIC-III dataset. It compares the outcomes with a segmentation model primarily based on the usual convolutional neural network (CNN) structure. The results reveal that the STN and RNN fashions gain superior overall performance compared to the usual CNN version in medical photograph segmentation. The look additionally highlights the capacity of deep studying fashions for addressing various demanding situations associated with clinical photograph segmentation. © 2024 IEEE.

关键词： architecture convolutional population Recurrent segmentation

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Enhancing Network Security with Blockchain technology

Enhancing Network Security with Blockchain Technology

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Inzimam Bishnoi, Amit Kumar Menaka, C. Vivekananda Global University Department of Computer Science & Application Jaipur India Teerthanker Mahaveer University Computing Sciences and Information Technology Uttar Pradesh Moradabad India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350383348

The block chain era is hastily traction as a sturdy approach to community security. In its conventional shape, block chain integrated is a distributed, immutable, and cryptographically-secured ledger, composed of virtual built in integrated shared amongst a disbursed community of nodes. This distributed ledger presents a platform for relaxed storage and verification of digital assets, built-inclusive of integrated crypto currencies, at the same time as built-integrated users with transactional privateness. As block chain-integrated technology advances, new applications, and protocols are built-integrated to resolve a variety of building situations related to network security. One such application is the utility of smart contracts to verify that community transactions are built-integrated, secure, and legitimate. By means of leverage building block chain integrated distributed ledger generation, clever contracts are capable of automating the execution of transactions at the same time as concurrently verifying their authenticity. This technique is built-in vital integrated fields of built finance and healthcare, as those built industries should manipulate and display access to treasured statistics and builtings. Moreover, smart contracts can be used to the right of entry to manage and authentication protocols, present built integrated customers with greater comfy get entry to data or sources. Any other use case there is for the deployment of distributed denial-of-carrier (DDoS) assault prevention protocols. DDoS attacks are one of the most luxurious and unfavorable online safety threats, and they use big amounts of bandwidth to crush a built in integrated or network-integrated infrastructure. © 2024 IEEE.

关键词： Bandwidth Contracts Conventional Generation Healthcare Infrastructure

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Bit level image encryption algorithm based on hyperchaotic system

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Optoelectronics Letters 2023年第3期19卷 186-192页

作者： MAN Zhenlong ZHANG Yue ZHOU Ying LU Xiaoli WANG Zhaoquan School of Electronic and Information Engineering Liaoning Technical UniversityHuludao 125100China Advanced Interactive Technology and Application Laboratory Computer Network Information CenterChinese Academy of SciencesBeijing 100190China

Because chaotic systems are unpredictable,ergodic and sensitive to initial values and parameters,they are often used in the field of *** avoid the bad randomness of the random key generated by the low dimensional chaotic map system,a 5-dimensional multi-wing hyperchaotic system is adopted in this *** key stream generated by the chaotic system is related to the plaintext *** it can effectively resist the attacks of selecting *** plaintext graph is decomposed into binary form by bit plane decomposition technique,and then these bit planes are divided into high and low *** designed control matrix is used to identify the specific scrambling mode,and each bit is permuted within and between ***,bit diffusion is used to change the pixel value of each *** analysis and numerical simulation show that the algorithm has good encryption performance for image encryption.

关键词： chaotic system algorithm

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Exploring the Impact of LSTM Parameters on Network Performance for Automatic Text Summarization

Exploring the Impact of LSTM Parameters on Network Performan...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Naaz, Rohaila Kavitha, R. Yadav, Surendra Teerthanker Mahaveer University Department of Computing Sciences and Information Technology Uttar Pradesh Moradabad India Department of Computer Science and Information Technology Bangalore India Vivekananda Global University Department of Computer Science & Application Jaipur India

ISBN: (纸本)9798350383348

This technical abstract explores the impact of extended quick-term reminiscence (LSTM) parameters on net overall performance for automated textual content summarization within the Korean language. It observes and considers the parameters of phrase embedding size, sentence length, and encoding intensity. Embedding length substantially affects the community's overall performance, and a pair of dimensional representations of word embedding can improve summarization accuracy. Increasing sentence duration additionally showed enhancements, with the very best accuracy executed at triple sentence embedding lengths. Eventually, encoding intensity had a low effect on network performance, with only barely better results visible with double and triple encodings. Overall, this observation concluded that gold standard network performance for textual content summarization in the Korean language is pleasant and finished via a mixture of two-dimensional embedding with an elevated sentence length and unmarried encoding intensity. © 2024 IEEE.

关键词： Embedding Encoding Enhancements Explores Low Effect Pleasant Summarization

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Combined CNN LSTM with attention for speech emotion recognition based on feature-level fusion

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Multimedia Tools and applications 2024年第21期83卷 59839-59859页

作者： Liu, Yanlin Chen, Aibin Zhou, Guoxiong Yi, Jizheng Xiang, Jin Wang, Yaru Institute of Artificial Intelligence Application College of Computer and Information Engineering Central South University of Forestry and Technology Hunan Changsha410004 China Hunan Key Laboratory of Intelligent Logistics Technology Central South University of Forestry and Technology Hunan Changsha410004 China

According to the problem that emotional features cannot be well represented by a single feature and it is difficult to extract in the task of Speech Emotion Recognition (SER), we propose a Feature-Level (FL) fusion method for 9 types of acoustic features and a combined CNN-LSTM network with attention (CNN-A-LSTM). The feature vector set after feature-level fusion is used as the input of CNN-A-LSTM network, which contains prosodic features and spectral features. High-level Statistical Functions (HSFs) are also added to receive global features. The feature extraction network CNN-A-LSTM can more effectively read time-series input and extract speech emotion information. Finally, Softmax is applied as a classifier to obtain the final emotion classification results. The experiment is verified on SAVEE and CASIA datasets. The experimental results show that the method in this paper has the best effect compared with the state-of-the-art, and the accuracy rates of 94.5% and 96.7% are respectively gained on SAVEE and CASIA. The above results prove the effectiveness of the algorithm in this paper with some generalization. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023.

关键词： Speech recognition

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