Results for 'Cloud Database'

520 found
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  1. A Review on Biometric Encryption System in Cloud Computing.Xiufeng Liu, Sheraz Arshad, Nosheen Nazir, Mubeen Fatima & Mahreen Mahi - 2018 - International Journal of Computer Science and Network Solutions 6 (1).
    This Review paper is about the security of bio metric templates in cloud databases. Biometrics is proved to be the best authentication method. However, the main concern is the security of the biometric template, the process to extract and stored in the database within the same database along with many other. Many techniques and methods have already been proposed to secure templates, but everything comes with its pros and cons, this paper provides a critical overview of these (...)
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  2.  32
    Conditional Entropy with Swarm Optimization Approach for Privacy Preservation of Datasets in Cloud.Sugumar R. - 2016 - Indian Journal of Science and Technology 9 (28):1-6.
    Background/Objective: The primary intension is to provide utility trade off and good privacy for intermediate datasets in cloud. Methods: An efficient conditional entropy and database difference ratio is employed for the process. Utility is taken care with the employment of conditional entropy with the help of Swarm Optimization (PSO). Privacy handled by database difference ratio. Findings: Conditional entropy is found out between the first column and the original database and this is taken as the fitness function (...)
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  3. Cloud Based Bookmark Manager.A. Sulaiman Suit - 2021 - Journal of Science Technology and Research (JSTAR) 2 (1):128-138.
    Cloud computing is the web-based empowering agent for sharing of mechanical infrastructural assets, programming, and computerized content, permitting them Infrastructure, Platforms, Software) to be offered on a compensation-for-use premise, similar to any utility assistance. Dramatic development in Computer capacities, the extra-conventional pace of development in advanced substance utilization, trailed by unstable development of uses have brought forth the beginning of Cloud Computing. The bookmarks which are saved offline can be only accessed by the specific system. The bookmarks are (...)
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  4. A Case Study on Transforming Legacy Databases Seamless Migration to Snowflake.Sankara Reddy Thamma - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):560-580.
    Migrating legacy database applications to modern cloud-based solutions, such as Snowflake, is becoming essential for organizations aiming to leverage scalable, efficient, and cost-effective data solutions. Legacy databases, typically bound to on-premises infrastructure, often lack the flexibility required by contemporary data analytics and storage needs. Snowflake, a cloud-native data platform, provides a versatile environment that enables efficient data storage, sharing, and processing. This research examines a structured methodology for migrating legacy database applications to Snowflake, addressing key stages (...)
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  5.  35
    EVALUATION OF TOP CLOUD SERVICE PROVIDERS' BI TOOLS: A COMPARISON OF AMAZON QUICKSIGHT, MICROSOFT POWER BI, AND GOOGLE LOOKER.Borra Praveen - 2024 - International Journal of Computer Engineering and Technology 15 (3):150-156.
    Business intelligence (BI) and data visualization tools play a pivotal role in today's businesses by facilitating data-driven decision-making. Amazon's AWS, Microsoft's Azure, and Google's GCP are the three foremost cloud service providers, providing extensive solutions encompassing computing, storage, databases, and advanced cloud services. This paper delivers a thorough comparative analysis of three top BI platforms: Amazon Studio, Microsoft Power BI, and Google Looker. It evaluates their features, user-friendliness, integration options, pricing structures, and customer support. By comparing specific features (...)
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  6. STC database for SQL Range Queries digital apps with Privacy Preserving.Chandran Sudhin - 2021 - Journal of Science Technology and Research (JSTAR) 2 (1):49-59.
    Businesses and people outsource database to realize helpful and low-cost applications and administrations. In arrange to supply adequate usefulness for SQL inquiries, numerous secure database plans have been proposed. In any case, such plans are helpless to protection leakage to cloud server. The most reason is that database is facilitated and handled in cloud server, which is past the control of information proprietors. For the numerical extend inquiry (“>”, “<”, etc.), those plans cannot give adequate (...)
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  7. Seamless Migration from Legacy Databases to Snowflake: A Comprehensive Case Study.P. Selvaprasanth - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):600-610.
    Migrating legacy database applications to modern cloud-based solutions, such as Snowflake, is becoming essential for organizations aiming to leverage scalable, efficient, and cost-effective data solutions. Legacy databases, typically bound to on-premises infrastructure, often lack the flexibility required by contemporary data analytics and storage needs. Snowflake, a cloud-native data platform, provides a versatile environment that enables efficient data storage, sharing, and processing. This research examines a structured methodology for migrating legacy database applications to Snowflake, addressing key stages (...)
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  8. Artificial intelligent smart home automation with secured camera management-based GSM, cloud computing and arduino.Musaddak Abdul Zahra & Laith A. Abdul-Rahaim Musaddak M. Abdul Zahra, Marwa Jaleel Mohsin - 2020 - Periodicals of Engineering and Natural Sciences 8 (4):2160-2168.
    Home management and controlling have seen a great introduction to network that enabled digital technology, especially in recent decades. For the purpose of home automation, this technique offers an exciting capability to enhance the connectivity of equipment within the home. Also, with the rapid expansion of the Internet, there are potentials that added to the remote control and monitoring of such network-enabled devices. In this paper, we had been designed and implemented a fully manageable and secure smart home automation system (...)
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  9. Integration of Internet Protocol and Embedded System On IoT Device Automation.Yousef MethkalAbd Algani, S. Balaji, A. AlbertRaj, G. Elangovan, P. J. Sathish Kumar, George Kofi Agordzo, Jupeth Pentang & B. Kiran Bala - manuscript
    The integration of Internet Protocol and Embedded Systems can enhance the communication platform. This paper describes the emerging smart technologies based on Internet of Things (IOT) and internet protocols along with embedded systems for monitoring and controlling smart devices with the help of WiFi technology and web applications. The internet protocol (IP) address has been assigned to the things to control and operate the devices via remote network that facilitates the interoperability and end-to-end communication among various devices c,onnected over a (...)
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  10.  24
    Secure Sharing of Personal Health Record in Cloud Environment.V. Tamilarasi E. Saranya - 2019 - International Journal of Innovative Research in Computer and Communication Engineering 7 (2):532-536.
    In cloud secure personal data sharing is the important issues because it creates several securities and data confidentiality problem while accessing the cloud services. Many challenges present in personal data sharing such as data privacy protection, flexible data sharing, efficient authority delegation, computation efficiency optimization, are remaining toward achieving practical fine-grained access control in the Personal Health Information Sharing system. Personal health records must be encrypted to protect privacy before outsourcing to the cloud. Aiming at solving the (...)
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  11.  96
    Unlocking Real-Time Analytics: A Case Study on Legacy Database Migration to Snowflake.A. Manoj Prabaharan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):590-600.
    The study outlines the technical challenges encountered during migration, including data compatibility issues, schema conversion, and security compliance, as well as strategies to mitigate these obstacles. Testing and validation techniques are applied throughout the migration, highlighting essential checkpoints to confirm data accuracy and optimal performance in the Snowflake environment. Postmigration performance metrics are evaluated to illustrate improvements in query execution, scalability, and overall system efficiency compared to the legacy system. The results underscore the advantages of Snowflake’s architecture in handling high-volume, (...)
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  12. Traducere şi traducători.Nicolae Sfetcu - 2014 - Drobeta Turnu Severin: MultiMedia Publishing.
    Include Ghidul Comisiei Europene pentru traducătorii din Uniunea Europeană Despre traducere şi traducători, teorii ale traducerilor, traducerea asistată pe calculator, şi software utilizat în traduceri. Include Ghidul Comisiei Europene pentru traducătorii din Uniunea Europeană şi legislaţia specifică traducerilor şi traducătorilor. Fidelitatea (sau loialitatea) şi transparenţa, idealurile duale în traducere, sunt de multe ori în conflict. Problema fidelităţii versus transparenţă a fost formulată şi în termeni de “echivalenţă formală” şi ” echivalenţă dinamică, sau funcţională“. Cele din urmă expresii sunt asociate cu (...)
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  13. Cloud computing and its ethical challenges.Matteo Turilli & Luciano Floridi - manuscript
    The paper analyses six ethical challenges posed by cloud computing, concerning ownership, safety, fairness, responsibility, accountability and privacy. The first part defines cloud computing on the basis of a resource-oriented approach, and outlines the main features that characterise such technology. Following these clarifications, the second part argues that cloud computing reshapes some classic problems often debated in information and computer ethics. To begin with, cloud computing makes possible a complete decoupling of ownership, possession and use of (...)
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  14.  24
    MULTI-CLOUD ENVIRONMENTS: MITIGATING SECURITY RISKS IN DISTRIBUTED ARCHITECTURES.Sharma Sidharth - 2021 - Journal of Artificial Intelligence and Cyber Security (Jaics) 5.
    The adoption of multi-cloud environments has become a strategic necessity for organizations seeking scalability, flexibility, and operational efficiency. However, distributing workloads across multiple cloud providers introduces significant security challenges, including authentication vulnerabilities, inconsistent security policies, data breaches, and compliance risks. Traditional security approaches often fail to address the complexity of multi-cloud ecosystems, requiring a more comprehensive risk mitigation strategy. This paper analyses key security risks in multi-cloud architectures and evaluates industry-standard risk assessment frameworks to prioritize effective (...)
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  15.  28
    SECURING CLOUD-NATIVE MICROSERVICES WITH SERVICE MESH TECHNOLOGIES.Sharma Sidharth - 2019 - Journal of Theoretical and Computationsl Advances in Scientific Research (Jtcasr) 3 (1):1-6.
    As cloud-native architectures continue to evolve, microservices have become the foundation for scalable and resilient applications. However, the decentralized nature of microservices introduces significant security challenges, including service-to-service communication security, identity management, and traffic control. Service mesh technologies, such as Istio, Linkerd, and Consul, provide a powerful solution by offering decentralized security enforcement, mutual TLS (mTLS) encryption, fine-grained access control, and observability without modifying application code. This paper explores how service meshes enhance microservices security by implementing zero-trust policies, automatic (...)
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  16. Secure Cloud Storage with Machine Learning-Optimized Attribute-Based Access Control Protocols.P. Selvaprasanth - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):420-435.
    This study examines how ABKS might optimize search efficiency and data security in cloud storage systems. We examine index compression, query processing improvement, and encryption optimization to decrease computational cost and preserve security. After a thorough investigation, the article shows how these methods may boost cloud storage system performance, security, and usability. Tests show that improved ABKS speeds up search searches and lowers storage costs, making it a viable cloud storage alternative. Exploring sophisticated machine learning algorithms for (...)
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  17.  73
    Cloud Migration Strategies for Mainframe Modernization: A Comparative Study of AWS, Azure, and GCP.Govindaraj Vasanthi - 2024 - International Journal of Computer Trends and Technology 72 (10):57-65.
    Mainframe systems have a track record of reliability, but they need help in today’s fast-changing business world. These include high upkeep expenses and limited room for growth. This paper looks at three top cloud platforms—Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP)—to update old mainframe programs. We compare them in detail, looking at what each does best. AWS has a wide range of tools to move data. Azure works well with cloud and on-site systems (...)
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  18.  18
    Cloud-based Document Collaboration System.Sayeda Raqeeba Banu Manjula K. - 2025 - International Journal of Innovative Research in Computer and Communication Engineering 13 (3):2071-2077.
    A Cloud-based Document Collaboration System (CDCS) enables multiple users to work together on documents in real time, leveraging the power of cloud computing to facilitate seamless and efficient collaboration. With increasing reliance on cloud technologies, such systems have revolutionized how teams, organizations, and individuals manage, edit, and share documents. This paper presents an overview of Cloud-based Document Collaboration Systems, focusing on the architecture, key features, benefits, challenges, and popular platforms. Additionally, we discuss the underlying technologies that (...)
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  19. SOLVING CLOUD VULNERABILITIES: ARCHITECTING AIPOWERED CYBERSECURITY SOLUTIONS FOR ENHANCED PROTECTION.Sanagana Durga Prasada Rao - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):84-90.
    The rapid adoption of cloud computing has revolutionized the way organizations operate, offering unparalleled flexibility, scalability, and efficiency. However, it also introduces a new set of vulnerabilities and security challenges. This manuscript explores the integration of artificial intelligence (AI) in cybersecurity solutions to address these cloud vulnerabilities. By examining the current landscape, AI methodologies, and practical implementation strategies, we aim to provide a roadmap for enhancing cloud security through AI-powered solutions. -/- .
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  20. Cloud-Based Secure Storage: A Framework for Efficient Encryption, Decryption, and Data Dispersion.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):427-434.
    The exponential growth of cloud storage has necessitated advanced security measures to protect sensitive data from unauthorized access. Traditional encryption methods provide a layer of security, but they often lack the robustness needed to address emerging threats. This paper introduces an optimized framework for secure cloud storage that integrates data encryption, decryption, and dispersion using cutting-edge optimization techniques. The proposed model enhances data security by first encrypting the data, then dispersing it across multiple cloud servers, ensuring that (...)
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  21.  32
    Cloud Architecture Design Patterns: Best Practices for Scalable and Secure Systems.Nivisha Govindaraj Ram Nivas Duraisamy - 2025 - International Journal of Multidisciplinary Research in Science, Engineering, Technology and Management 12 (3):691-697.
    Cloud computing has transformed how businesses design, deploy, and manage applications. With its ability to provide on-demand resources and scalability, cloud platforms offer significant benefits in terms of flexibility, cost-efficiency, and speed. However, to fully leverage these advantages, it is crucial to apply proven design patterns that ensure the cloud architecture is both scalable and secure. This paper explores key cloud architecture design patterns, including microservices, serverless architecture, multi-cloud, and hybrid cloud, along with best (...)
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  22.  28
    How Cloud Computing Revolutionizes Human Capital Management.Harish Kumar Reddy Kommera - 2019 - Turkish Journal of Computer and Mathematics Education (TURCOMAT) 10 (2):2018-2031.
    The advent of cloud computing has fundamentally transformed various business operations, with Human Capital Management (HCM) standing out as a significant beneficiary. Cloud-based HCM solutions offer unparalleled scalability, accessibility, and integration capabilities, enabling organizations to manage their workforce more efficiently and strategically. This paper explores the revolutionary impact of cloud computing on HCM, highlighting key advancements such as enhanced data analytics, improved employee engagement, cost-effectiveness, and support for remote and hybrid work models. Through a comprehensive literature review (...)
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  23. The Ethics of Cloud Computing.Boudewijn De Bruin & Luciano Floridi - 2017 - Science and Engineering Ethics 23 (1):21-39.
    Cloud computing is rapidly gaining traction in business. It offers businesses online services on demand (such as Gmail, iCloud and Salesforce) and allows them to cut costs on hardware and IT support. This is the first paper in business ethics dealing with this new technology. It analyzes the informational duties of hosting companies that own and operate cloud computing datacenters (e.g., Amazon). It considers the cloud services providers leasing ‘space in the cloud’ from hosting companies (e.g, (...)
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  24. Cloud Computing and Big Data for Oil and Gas Industry Application in China.Yang Zhifeng, Feng Xuehui, Han Fei, Yuan Qi, Cao Zhen & Zhang Yidan - 2019 - Journal of Computers 1.
    The oil and gas industry is a complex data-driven industry with compute-intensive, data-intensive and business-intensive features. Cloud computing and big data have a broad application prospect in the oil and gas industry. This research aims to highlight the cloud computing and big data issues and challenges from the informatization in oil and gas industry. In this paper, the distributed cloud storage architecture and its applications for seismic data of oil and gas industry are focused on first. Then, (...) desktop for oil and gas industry applications are also introduced in terms of efficiency, security and usability. Finally, big data architecture and security issues of oil and gas industry are analyzed. Cloud computing and big data architectures have advantages in many aspects, such as system scalability, reliability, and serviceability. This paper also provides a brief description for the future development of Cloud computing and big data in oil and gas industry. Cloud computing and big data can provide convenient information sharing and high quality service for oil and gas industry. (shrink)
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  25. OPTIMIZED CLOUD SECURE STORAGE: A FRAMEWORK FOR DATA ENCRYPTION, DECRYPTION, AND DISPERSION.S. Yoheswari - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):415-426.
    The exponential growth of cloud storage has necessitated advanced security measures to protect sensitive data from unauthorized access. Traditional encryption methods provide a layer of security, but they often lack the robustness needed to address emerging threats. This paper introduces an optimized framework for secure cloud storage that integrates data encryption, decryption, and dispersion using cutting-edge optimization techniques. The proposed model enhances data security by first encrypting the data, then dispersing it across multiple cloud servers, ensuring that (...)
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  26.  44
    The Rise of Learning Cloud Technologies: Empowering the Digital Transformation.Akula Arvind Kumar - 2024 - International Journal of Innovative Research in Science, Engineering and Technology 13 (8):14671-14679.
    This comprehensive article explores the convergence of cloud computing and Java technologies, highlighting their synergistic relationship in modern software development. It examines key concepts in cloud computing, including virtualization, microservices architecture, CI/CD practices, and serverless computing. The article also discusses various cloud service models (SaaS, PaaS, and IaaS), their applications, and essential tools and technologies for cloud development. A financial institution's infrastructure modernization case study illustrates the practical implementation of these concepts, demonstrating how cloud technologies (...)
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  27. EFFICIENT STRATEGIES FOR SEAMLESS CLOUD MIGRATIONS USING ADVANCED DEPLOYMENT AUTOMATIONS.Tummalachervu Chaitanya Kanth - 2023 - Journal of Science Technology and Research (JSTAR) 4 (1):61-70.
    The increasing complexity and scale of modern computing needs have led to the development and adoption of cloud computing as a ubiquitous paradigm for data storage and processing. The hybrid cloud model, which combines both public and private cloud infrastructures, has been particularly appealing to organizations that require both the scalability offered by public clouds and the security features of private clouds. Various strategies for configuring and managing resources have been developed to optimize the hybrid cloud (...)
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  28. Cloud Data Security Using Elliptic Curve Cryptography.Arockia Panimalars, N. Dharani, R. Aiswarya & Pavithra Shailesh - 2017 - International Research Journal of Engineering and Technology 9 (4).
    Data security is, protecting data from ill- conceived get to, utilize, introduction, intrusion, change, examination, recording or destruction. Cloud computing is a sort of Internet-based computing that grants conjoint PC handling resources and information to PCs what's more, different gadgets according to necessity. It is a model that empowers universal, on-request access to a mutual pool of configurable computing resources. At present, security has been viewed as one of the best issues in the improvement of Cloud Computing. The (...)
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  29. CSsEv: Modelling QoS Metrics in Tree Soft Toward Cloud Services Evaluator based on Uncertainty Environment.Mona Gharib, Florentin Smarandache & Mona Mohamed - 2024 - International Journal of Neutrosophic Science 23 (2):32-41.
    Cloud computing (ClC) has become a more popular computer paradigm in the preceding few years. Quality of Service (QoS) is becoming a crucial issue in service alteration because of the rapid growth in the number of cloud services. When evaluating cloud service functioning using several performance measures, the issue becomes more complex and non-trivial. It is therefore quite difficult and crucial for consumers to choose the best cloud service. The user's choices are provided in a quantifiable (...)
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  30.  97
    Cloud-Enabled Risk Management of Cardiovascular Diseases Using Optimized Predictive Machine Learning Models.Kannan K. S. - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):460-475.
    Data preparation, feature engineering, model training, and performance evaluation are all part of the study methodology. To ensure reliable and broadly applicable models, we utilize optimization techniques like Grid Search and Genetic Algorithms to precisely adjust model parameters. Features including age, blood pressure, cholesterol levels, and lifestyle choices are employed as inputs for the machine learning models in the dataset, which consists of patient medical information. The predictive capacity of the model is evaluated using evaluation measures, such as accuracy, precision, (...)
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  31.  37
    Reliability Engineering in Cloud Computing: Strategies, Metrics, and Performance Assessment.Anand Karanveer - 2023 - International Journal of Multidisciplinary Research in Science, Engineering and Technology 6 (12):3451-3464.
    Cloud computing has transformed the nature of computation, sharing of information resources, and storage capabilities, including the flexibility to scale these resources for corporate use. Nevertheless, maintaining high reliability in cloud environments is still an issue that has not been solved because of factors such as Hardware failures, network interruptions/slowdowns and software vulnerabilities. This paper discusses several methods that can be employed in the reliability engineering of cloud computing, including fault tolerance, redundancy, monitoring and predictive maintenance. It (...)
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  32. Cloud Computing for Space Exploration: Enabling Data-Intensive Research and Remote Operations Beyond Earth.Hirulkar Sakshi R. - 2025 - International Journal of Multidisciplinary Research in Science, Engineering and Technology (Ijmrset) 8 (1):371-376.
    As space exploration advances, the need for innovative technologies to handle the ever-growing data and facilitate remote operations beyond Earth becomes critical. Cloud computing is emerging as a transformative force in space missions, enabling data-intensive research, remote collaboration, and the management of large datasets from space missions. This paper explores the role of cloud computing in space exploration, focusing on its potential to support the growing complexity of space missions, improve data storage and processing, and enable real-time remote (...)
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  33. Cloud Computing in the Circular Economy:Redefining Resource Efficiency and Waste Reduction for Sustainable Business Practices.Dwivedi Shashi - 2025 - International Journal of Advanced Research in Arts, Science, Engineering and Management (Ijarasem) 12 (1):348-352.
    The transition to a Circular Economy (CE) is a critical strategy in addressing global challenges related to resource depletion, waste generation, and environmental sustainability. Cloud computing, as a scalable and data-driven technology, has a significant role to play in enabling the circular economy by enhancing resource efficiency, waste reduction, and the optimization of product lifecycles. This paper explores how cloud computing facilitates circular economy practices by leveraging advanced technologies such as data analytics, Internet of Things (IoT), and Artificial (...)
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  34. Cloud-Native Security Frameworks: AIDriven Risk Mitigation Strategies for MultiCloud Environments.Tripathi Praveen - 2023 - International Journal of Innovative Research in Science, Engineering and Technology 12 (11):13144-13146.
    The growing adoption of cloud computing has necessitated the development of AI-driven security frameworks to address threats in multi-cloud environments. This paper presents a cloud-native security model leveraging AI and zero-trust principles to enhance compliance, risk monitoring, and threat mitigation.
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  35. Sustainable Cloud Computing: Achieving NetZero Carbon Emissions in Data Centers.Deepak Ramchandani Taman Poojary - 2024 - International Journal of Multidisciplinary Research in Science, Engineering and Technology 8 (3):1720-1725.
    Cloud computing is revolutionizing modern computing infrastructure, but as the demand for cloud services grows, so does the energy consumption of the data centers that support them. Data centers, which house the servers that power cloud computing, are significant contributors to global carbon emissions. This paper explores strategies to achieve net-zero carbon emissions in data centers, focusing on energy efficiency, renewable energy integration, and carbon offsetting practices. The paper reviews current technologies, practices, and policies aimed at reducing (...)
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  36. ADVANCE DATA SECURITY IN CLOUD NETWORK SYSTEMS.Tummalachervu Chaitanya Kanth - 2023 - Journal of Science Technology and Research (JSTAR) 4 (1):29-36.
    This research presents a novel and efficient public key cryptosystem known as the Enhanced Schmidt Samoa (ESS) cryptosystem, proposed to safeguard the data of a single owner in cloud computing environments. Data storage is a one-time process in the cloud, while data retrieval is a frequent operation. Experimental results demonstrate that the ESS cryptosystem offers robust data confidentiality in the cloud, surpassing the security provided by traditional cryptosystems. The research also introduces a secure cloud framework designed (...)
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  37.  50
    COMPARATIVE REVIEW: TOP CLOUD SERVICE PROVIDERS ETL TOOLS - AWS VS. AZURE VS. GCP.Borra Praveen - 2024 - International Journal of Computer Engineering and Technology 15 (3):203-208.
    ETL (Extract, Transform, Load) tools play a crucial role in contemporary data management by enabling the extraction, transformation, and loading of data from various sources into designated systems for analysis and reporting purposes. Major cloud service providers including Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) give robust ETL solutions tailored to diverse business needs. This document presents a comparative assessment of the primary ETL tools offered by AWS, Azure, and GCP—namely, AWS Glue, Amazon Data (...)
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  38.  26
    Streamlining HCM Processes with Cloud Architecture.Harish Kumar Reddy Kommera - 2020 - Turkish Journal of Computer and Mathematics Education (TURCOMAT) 11 (2):1323-1338.
    The integration of cloud architecture into Human Capital Management (HCM) systems has revolutionized the way organizations manage their workforce. Cloud-based HCM solutions offer enhanced scalability, flexibility, and accessibility, enabling organizations to streamline HR processes, improve data management, and foster greater employee engagement. This paper explores the impact of cloud architecture on HCM processes, highlighting key benefits such as cost-effectiveness, real-time data access, and seamless integration with other business systems. Through a comprehensive literature review and analysis of case (...)
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  39.  27
    Multi-Cloud Data Resilience: Implementing Cross-Platform Data Strategies with Snowflake for P&C Insurance Operations.Adavelli Sateesh Reddy - 2023 - International Journal of Science and Research 12 (1):1387-1398.
    Property and Casualty (P&C) insurers are adopting multi-cloud environments as a strategic imperative because of their increasing data volumes and complexities in regulatory compliance, customer expectations and technological advancements. This paper discusses how Snowflake’s cloud-agnostic, unified platform enables insurers to create resilient, efficient, and compliant multi cloud data strategies. Using Snowflake’s elastic scalability, real-time analytics, secure data sharing and seamless cloud interoperability, insurers can optimize claims processing, augment fraud detection, and support customer engagement. The study offers (...)
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  40. Autonomous Cloud Operations: Self-Optimizing Cloud Systems Powered By AI and Machine Learning.G. Geethanjali - 2013 - International Journal of Innovative Research in Computer and Communication Engineering 13 (3):2138-2143.
    The exponential growth of cloud computing has revolutionized the IT industry by providing scalable, flexible, and cost-efficient infrastructure solutions. However, as cloud systems become more complex, managing and optimizing these environments becomes increasingly challenging. Traditional cloud management methods often require manual intervention and significant resources to maintain performance, cost-efficiency, and security. Autonomous cloud operations, powered by artificial intelligence (AI) and machine learning (ML), represent the next frontier in cloud management. By leveraging advanced algorithms and real-time (...)
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  41.  46
    Microsoft Azure Networking: Empowering Cloud Connectivity and Security.Borra Praveen - 2024 - International Journal of Advanced Research in Science, Communication and Technology 4 (3):469-475.
    In the current era dominated by cloud computing, networking infrastructure serves as the backbone of digital operations. Among the top cloud service providers, Microsoft Azure offers a robust suite of networking solutions tailored to meet the evolving needs of modern businesses. This document aims to provide a comprehensive overview of Azure networking, examining its key components, deployment models, best practices, and practical applications. By exploring Azure Virtual Network, Load Balancer, VPN Gateway, ExpressRoute, Firewall, and other services in detail, (...)
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  42. AI-POWERED THREAT INTELLIGENCE FOR PROACTIVE SECURITY MONITORING IN CLOUD INFRASTRUCTURES.Tummalachervu Chaitanya Kanth - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):76-83.
    Cloud computing has become an essential component of enterprises and organizations globally in the current era of digital technology. The cloud has a multitude of advantages, including scalability, flexibility, and cost-effectiveness, rendering it an appealing choice for data storage and processing. The increasing storage of sensitive information in cloud environments has raised significant concerns over the security of such systems. The frequency of cyber threats and attacks specifically aimed at cloud infrastructure has been increasing, presenting substantial (...)
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  43.  93
    Scalable Cloud Solutions for Cardiovascular Disease Risk Management with Optimized Machine Learning Techniques.A. Manoj Prabaharan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):454-470.
    The predictive capacity of the model is evaluated using evaluation measures, such as accuracy, precision, recall, F1-score, and the area under the ROC curve (AUC-ROC). Our findings show that improved machine learning models perform better than conventional methods, offering trustworthy forecasts that can help medical practitioners with early diagnosis and individualized treatment planning. In order to achieve even higher predicted accuracy, the study's conclusion discusses the significance of its findings for clinical practice as well as future improvements that might be (...)
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  44.  38
    An effective encryption algorithm for multi-keyword-based top-K retrieval on cloud data.R. Sugumar - 2016 - Indian Journal of Science and Technology 9 (48):1-5.
    Cloud Computing provides vast storage facility. The requirement of this system is to improve the security and transmission performance in the cloud storage environment. Methods: This system provides two level of security for the cloud data. The Client Data Security Contrivance (CDSC) and Cloud Service Provider (CSP) Data Security Contrivance are the two methods which transforms the original data to cipher text. The security algorithm used in CDSC is Linguistic Steganography. Blowfish algorithm is used in CSP (...)
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  45. Cloud-Native Quantum Computing: Unlocking the Potential of Quantum Algorithms on Cloud Infrastructure.Kanchan C. Gaikwad Sakshi R. Hirulkar - 2025 - International Journal of Multidisciplinary and Scientific Emerging Research (Ijmserh) 13 (1):261-264.
    Quantum computing has the potential to revolutionize problem-solving across various domains, from cryptography to materials science. However, the complexities of quantum hardware, including the need for highly specialized environments and significant computational resources, have made quantum computing difficult for most organizations to access. Cloud-native quantum computing, which leverages cloud infrastructure to provide scalable, ondemand access to quantum processors, offers a transformative solution to this challenge. This paper explores the rise of cloud-native quantum computing, focusing on how (...) infrastructure facilitates the deployment and execution of quantum algorithms. We examine the benefits of cloud-based quantum computing, the challenges it faces, and the role of cloud service providers in advancing quantum technologies. Additionally, we explore the synergy between quantum computing and classical computing, emphasizing hybrid quantum-classical systems. Finally, we look ahead to the future of quantum computing in the cloud, outlining emerging trends, research opportunities, and the potential impacts on industries such as finance, healthcare, and logistics. (shrink)
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  46.  41
    Enhancing Cloud Security with AI-Based Intrusion Detection Systems.Sharma Sidharth - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):658-664.
    Cloud computing has transformed data management by providing scalable and on-demand services, but its open and shared infrastructure makes it highly vulnerable to sophisticated cyber threats. Traditional Intrusion Detection Systems (IDS) struggle with dynamic and large-scale cloud environments due to high false positives, limited adaptability, and computational overhead. To address these challenges, this paper proposes an AI-driven Intrusion Detection System (AI-IDS) that leverages deep learning models, including Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks, to analyze (...)
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  47.  49
    A Proficient Two Level Security Contrivances for Storing Data in Cloud.R. Sugumar K. Anbazhagan - 2016 - Indian Journal of Science and Technology 9 (48):1-5.
    Cloud Computing provides vast storage facility. The requirement of this system is to improve the security and transmission performance in the cloud storage environment. Methods: This system provides two level of security for the cloud data. The Client Data Security Contrivance (CDSC) and Cloud Service Provider (CSP) Data Security Contrivance are the two methods which transforms the original data to cipher text. The security algorithm used in CDSC is Linguistic Steganography. Blowfish algorithm is used in CSP (...)
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  48. Machine Learning-Enhanced Secure Cloud Storage with Attribute-Based Data Access.A. Manoj Prabaharan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):418-429.
    Cloud computing has transformed data management and storage by providing unmatched scalability, flexibility, and cost-effectiveness. However, rising cloud storage use has raised data security and privacy issues. As sensitive data being outsourced to third-party cloud providers, security is crucial. Traditional encryption methods secure data but make data recovery difficult. Specifically, efficiently searching encrypted data without compromising security is difficult.
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  49. A Shift from Cloud Computing Model to Fog Computing.C. Sailesh & S. Svermani - 2016 - Journal of Applied Computing 1 (1).
    Cloud computing has provided many opportunities to businesses and individuals. It enables global and on demand network access to a shared pool of resources with minimal management effort. However, this bliss has become a problem for latency-sensitive applications. To improve efficiency of cloud and to reduce the amount of data that needs to be transported to the cloud for data processing, analysis and storage, a new network architect technology 'Fog Computing' has been introduced. In fog computing, small (...)
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  50.  63
    ntelligent Hybrid Cloud Data Deduplication for Optimized Storage Utilization.A. Manoj Prabaharan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):625-633.
    The framework leverages a hybrid cloud architecture, combining the scalability of public clouds with the security of private clouds. By employing a combination of client-side hashing, metadata indexing, and machine learning-based duplicate detection, the framework achieves significant storage savings without compromising data integrity. Real-time testing on a hybrid cloud setup demonstrated a 65% reduction in storage needs and a 40% improvement in data retrieval times. Additionally, the system employs blockchain for immutable logging of deduplication activities, enhancing transparency and (...)
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