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 (...) issues and solutions. (shrink)

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 (...) in Particle Swarm Optimization (PSO). Database difference is taken between the original database and convoluted database in the consequent module to yield right selection data and tuple information from the intermediate datasets in cloud. Applications/Improvements: Improved methods are required to provide privacy and utility for the right selection of datasets. This approach has better results by having higher entropy values and lower dataset difference ratio. (shrink)

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 (...) stored in the cloud using platform-as-a-service. Platform-as-a-service (PaaS) is the following layer up – just as the basic stockpiling, organizing, and virtual servers this will likewise incorporate the instruments and programming that designers need to assemble applications on top of: that could incorporate middleware, database management, operating system, and development tools. (shrink)

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 (...) from initial assessment to data transformation, integration, and performance optimization. A systematic, step-by-step migration process is implemented to minimize risks, reduce downtime, and ensure data integrity. (shrink)

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 (...) and examining real-world applications, this paper offers bits of knowledge that will assist organizations with picking the best tool to meet their particular requirements. The objective is to aid businesses and professionals in comprehending the strengths and weaknesses of each platform, thereby enabling them to make informed choices tailored to their unique needs. (shrink)

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 (...) protection security against viable challenges, e.g., security spillage of measurable properties, get to design. Besides, expanded number of questions will definitely spill more data to the cloud server. In this paper, we propose a two-cloud engineering for secure database, with a arrangement of crossing point conventions that give security conservation to different numeric-related extend questions. Security analysis shows that privacy of numerical information is strongly protected against cloud providers in our proposed scheme. (shrink)

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 (...) from initial assessment to data transformation, integration, and performance optimization. A systematic, step-by-step migration process is implemented to minimize risks, reduce downtime, and ensure data integrity. (shrink)

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 (...) based on a cloud computing system with an ESP Arduino system. The security of home had been improved by adding a complete camera system with a GSM communication technique to connect the Arduino output data to an external specified number if there is no internet provider. We used three sensors for temperature, gas, and motion measurements. The ESP8226 Wi-Fi device programmed the sensors to maintain the sensors measurements and transfer them to the cloud server database which is programmed to the web server via Appatshy and Mysql formats. The system implemented with high time response so that all readings updated and appeared spontaneously. The designed system should be effective, a secure, and rapid response real-time smart home system should be achieved. (shrink)

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 (...) network. The HTTP POST and HTTP GET command that supports the RESTful service have been used to ensure the transmission and reception of packets between the IOT Gateway and Cloud Database. The emerging smart technologies based on the Internet of Things (IoT) facilitated features like automation, controllability, interconnectivity, reliability which in turn turn paved the way for a wide range of acceptance amongst the masses. The Internet of Things (IoT) has brought in many new emerging technologies into varoius field like our daily lives, industry, agricultural sector, and many more. The world is experiencing the explosive growth with the advent of Internet of Things (IoT) these years. The potential growth of IoT is enoromous which is evidenced by all the human beings in our day to day life. (shrink)

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 (...) above challenges, here propose an efficient data sharing mechanism for Personal Data Sharing, which not only achieves data privacy, fine-grained access control and authority delegation simultaneously, but also optimizes the computation efficiency and is suitable for resource constrained servers. Most of the data consumers are honest, while few of them are corrupt and will leakage their secret keys in the collusion. On the contrary, PKG and data owner are assumed to be fully trusted. Besides, public cloud 1 and public cloud 2 cannot collude with each other. The non-collusive assumption is reasonable, because the client can demand that two cloud servers cannot reveal users’ information by contract. In proposed work, PR-ABE (Attribute Based Encryption with Proxy Re-encryption) technique implements to provide secure encryption of medical data. To improve the access control, here partial key sharing scheme will be implement. Using this, data owner can send partial secret key for the requested user. This approach overcomes the key guessing attack in data retrieval process. (shrink)

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, (...) concurrent queries without compromising speed or accuracy. (shrink)

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 (...) traducătorul Eugene Nida şi au fost iniţial inventate pentru a descrie modalităţi de traducere a Bibliei, dar cele două abordări sunt aplicabile la orice traducere. În general, traducători au căutat să păstreze contextul în sine prin reproducerea ordinei iniţiale a sememelor, şi, prin urmare, ordinea cuvintelor - atunci când este necesar, reinterpretarea structurii gramaticale reale, de exemplu prin trecerea de la starea activă la cea pasivă sau invers. Diferenţele gramaticale dintre limbile cu "ordinea fixă a cuvânului" (engleză, franceză, germană) şi limbile cu "ordinea liberă a cuvântului" (de exemplu, greacă, latină, poloneză, rusă) nu a fost un impediment în acest sens. Caracteristicile sintaxei speciale (propoziţie-structură) a textului în limba sursă sunt adaptate la cerinţele sintactice ale limbii ţintă. Rolul traducătorului în legătură cu un text a fost comparată cu cea a unui artist, de exemplu, un muzician sau actor, care interpretează o lucrare de artă. Traducerea, ca şi alte arte, implică inevitabil alegeri, şi alegerea implică interpretare. CUPRINS: Traduceri - Teorii - - Teoria occidentală a traducerilor - - Tradiţii mai puţin răspândite - - - Orientul Apropiat antic - - - Orient - - - Lumea islamică - Fidelitate versus transparenţă în traduceri - Echivalenţa în traduceri - Traducerea inversă - Traducători - - Traducători interpreţi - - - Notiţe folosite de traducătorii interpreţi - - Traducere umană sau traducere automată pe Internet? - - Traducerea asistată de calculator - Traducerea automată - Traducerea literară - - Traducerea poeziilor - - Traducerea textelor cântecelor - - Traducerea textelor religioase - Traducerea colaborativă - - Relaţia cu cloud computing - Nedeterminarea traducerilor - - Nedeterminarea referinţei - - Nedeterminarea holofrazică - - Observaţii generale - - Distincţie analitic-sintetică - Glosa interliniară - - Structura - - Punctuaţia Traducerea homofonică - Versurile cântecelor - Subtitrarea - - Crearea, livrarea şi afişarea de subtitrări - - Traducerea subtitrată - - - Subtitrarea Internaţionalizare şi localizare - Diferenţe în procesele de internaţionalizare şi localizare în traduceri - Localizarea - - Internaţionalizare, globalizare, localizare - - - Traducere versus localizare - - - Globalizarea versus localizare - - Etichete de limbă şi coduri - Localizarea site-urilor web - - Procesul - - Localizarea în zona de administrare - - Afacerea localizării site-ului - Localizarea jocurilor - - Sarcini şi provocări - - Valori lingvistice - - Tipuri de text şi formate de fişiere - - - Manual - - - Ambalaj - - - Fişier ajutător (readme) - - - Site-ul oficial - - - Dialog pentru dublaj - - - Dialog pentru subtitrare - - - Interfaţa utilizator - - - Arta grafică cu cuvinte - Localizarea socială - - Obiective - - - Localizarea comercială şi necomercială - Pseudolocalizarea - - Procesul de localizare - - Pseudolocalizarea în Microsoft Windows - - Procesul de pseudolocalizare la Microsoft - - Instrumente de pseudolocalizare pentru alte platforme Traduceri asistate de calculator - Aplicaţii - Concepte în traducerea asistată pe calculator - - Software de memorare a traducerii - - Software de limbaj ale motoarelor de căutare - - Software de gestionare a terminologiei - - Software de aliniere - - Traducere automată interactivă - - Traducere colaborativă - Software pentru traducerea asistată pe calculator - - Software - - Formate de fişiere suportate - - SO - - Licenţa - - GlobalSight - - gtranslator - - Lokalize - - MemSource - - MetaTexis - - OmegaT - - Open Language Tools - - Poedit - - Pootle - - SDL Trados - - TM-database - - Virtaal - - Wordfast PRO - - XTM Cloud - Traduceri în/din limba română cu Miscrosoft Word Traducerea automată - Abordări în traducerea automată - - Traduceri automate pe bază de reguli - - - Traduceri automate pe bază de transfer - - - Traduceri automate interlinguale - - - Traduceri automate pe bază de dicţionar - - Traducere automată statistică - - Traducere automată pe bază de exemple - - Traducere automată hibridă Baze de date - Terminologia Interactivă pentru Europa - - Eurodicautom - Google Translator Toolkit - BabelNet - - Statistica BabelNet - - Aplicaţii Dicţionare - Dicţionare bilingve - - Istoria - - Utilizare - - Formate - - Distribuţia - - Dicţionare multilingve - Provocări în domeniul dicţionarelor bilingve - Cărţi de fraze (Ghiduri de conversaţie) - - Structura - - De notat Legea nr. 178/1997 Ghidul UE - Întâi reflectaţi, apoi redactaţi - - Cine va citi documentul? - - Care este rezultatul urmărit? - - Ce trebuie să includă documentul dumneavoastră? - Cititorul are întâietate - - Stil direct şi interesant - Organizaţi documentul - - La început - - Pe parcursul redactării - SOS: Scurt, la obiect şi simplu - - Scurt, la obiect… - - ... şi simplu - - Un stil simplu şi neîncărcat înseamnă, de asemenea: - Fiţi logici – structuraţi-vă frazele - Evitaţi substantivele inutile – formele verbale sunt mai dinamice - Fiţi concreţi, evitaţi abstractizările - Optaţi pentru diateza adecvată - - Acolo unde este necesar, precizaţi agentul - Evitaţi „prietenii falşi”, jargonul, acronimele şi siglele - - Evitaţi „prietenii falşi” - - Evitaţi sau explicaţi jargonul - - Fiţi atenţi la acronime şi sigle - - Înainte de final, revizuiţi şi verificaţi - - Aveţi nevoie de ajutor? Citate Referinţe Despre autor - Nicolae Sfetcu - - De același autor - - Contact Editura - MultiMedia Publishing. (shrink)

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 (...) data and this helps to explain the problems occurring when different providers of cloud computing retain or relinquish the right to use or own users‘ data. The problem of safety in cloud computing is coupled to that of reliability, insofar as users have to trust providers to preserve their data, applications and content in a reliable manner. It is argued that, in this context, data insurance could play an important role. Regarding fairness, the paper argues that cloud computing is already reshaping the nature of the Digital. Responsibility, accountability and privacy close the ethical analysis of cloud computing. In this case, the thesis is that the necessity to account for the actions of cloud computing users imposes delicate trade-offs between users‘ privacy and the traceability of their operations. (shrink)

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 (...) countermeasures. Our findings indicate that authentication, access control, and secure cloud networking are the most critical areas requiring immediate attention. Threats such as identity mismanagement, insecure data transfers, and lack of unified monitoring further escalate security concerns. To mitigate these risks, we propose a combination of zero-trust architecture, robust identity and access management (IAM), encryption protocols, and AI-driven threat detection. Implementing these strategies can enhance data integrity, regulatory compliance, and overall cloud security posture. By adopting a proactive approach, IT leaders can optimize cybersecurity investments and ensure the resilience of multi-cloud environments. This study provides actionable insights to strengthen security in distributed cloud architectures, enabling organizations to defend against evolving cyber threats. (shrink)

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 (...) traffic encryption, and service authentication mechanisms. Through the integration of policy-based access control, workload identity, and anomaly detection, service mesh architectures significantly reduce the risk of unauthorized access, lateral movement attacks, and data breaches. Additionally, this study highlights best practices for deploying secure service meshes in cloud-native environments, ensuring compliance with industry security standards. The findings demonstrate that adopting a service mesh improves security posture while maintaining agility and performance in microservices-based applications. (shrink)

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 (...) predictive search improvements a. (shrink)

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 (...) and fits into company setups. GCP leads in AI and machine learning. Azure is the top option for updating mainframes, offering compatibility with various cloud configurations, integration with current company infrastructure, and sophisticated data analysis driven by AI. These conclusions provide valuable information for companies transitioning mainframe systems to the cloud, enabling expansion, reduced expenses, and future-ready IT systems. (shrink)

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 (...) enable collaboration, including cloud storage, version control, and real-time synchronization. The paper highlights key use cases, compares leading platforms, and examines potential future trends in cloud-based document collaboration. (shrink)

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. -/- .

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 (...) no single server holds the complete dataset. Decryption occurs only when the dispersed data fragments are reassembled, which adds an additional layer of security. We also explore various optimization algorithms to improve the efficiency of encryption and dispersion processes, thereby reducing computational overhead while maintaining high security. (shrink)

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 (...) practices for achieving scalable and secure systems. Emphasizing security and scalability, it provides guidance for organizations on how to build resilient and high-performing cloud systems. (shrink)

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 (...) and analysis of case studies from diverse industries, the study demonstrates how cloud computing facilitates real-time data access, seamless system integration, and the implementation of advanced technologies like artificial intelligence (AI) and machine learning (ML) within HCM frameworks. Additionally, the research addresses challenges associated with cloud-based HCM adoption, including data security, privacy concerns, and change management. Future research directions are proposed to further leverage cloud computing capabilities, emphasizing the integration of emerging technologies and the continuous evolution of cloud-based HCM tools. The findings underscore the pivotal role of cloud computing in enhancing organizational agility, optimizing human capital, and driving sustainable business growth. (shrink)

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, (...) Dropbox, Salesforce). And it examines the business and private ‘clouders’ using these services. The first part of the paper argues that hosting companies, services providers and clouders have mutual informational (epistemic) obligations to provide and seek information about relevant issues such as consumer privacy, reliability of services, data mining and data ownership. The concept of interlucency is developed as an epistemic virtue governing ethically effective communication. The second part considers potential forms of government restrictions on or proscriptions against the development and use of cloud computing technology. Referring to the concept of technology neutrality, it argues that interference with hosting companies and cloud services providers is hardly ever necessary or justified. It is argued, too, however, that businesses using cloud services (banks, law firms, hospitals etc. storing client data in the cloud, e.g.) will have to follow rather more stringent regulations. (shrink)

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, (...) class='Hi'>cloud 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)

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 (...) no single server holds the complete dataset. Decryption occurs only when the dispersed data fragments are reassembled, which adds an additional layer of security. We also explore various optimization algorithms to improve the efficiency of encryption and dispersion processes, thereby reducing computational overhead while maintaining high security. The implementation of this framework is evaluated on multiple cloud platforms, demonstrating its effectiveness in safeguarding data with minimal performance impact. Future enhancements may include integrating machine learning algorithms to predict and adapt to new security threats in real time, further solidifying the reliability of cloud storage solutions. (shrink)

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 (...) and Java can enhance agility, reliability, cost-efficiency, and innovation in traditional industries. (shrink)

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 (...) environment. These strategies aim to balance conflicting objectives such as cost-efficiency, performance optimization, security, and compliance with regulatory standards. This exploratory research focused on evaluating the efficiency and limitations of different configuration strategies in hybrid cloud environments. Findings indicate that each approach presents distinct advantages. Improving resource utilization and automating governance processes are significant advantages of Policy-based Resource Management, which leads to costeffectiveness. Intelligent routing of traffic is a feature of Cross-cloud Load Balancing, resulting in optimized performance and higher service availability. By centralizing control, the Hybrid Cloud Service Mesh allows for secure and streamlined cross-service communication. A notable feature of Cross-cloud Container Orchestration is its ability to simplify the migration of applications across diverse cloud environments. For immediate threat detection and regulatory compliance, real-time monitoring is facilitated by Log Management and Analytics. However, Policy-based Resource Management can be complex and inflexible. Extra costs for data transfer between different cloud providers are a drawback of Crosscloud Load Balancing. Additional network hops create latency issues in Hybrid Cloud Service Mesh configurations. If configured incorrectly, Cross-cloud Container Orchestration could expose the system to security risks. Finally, Log Management and Analytics require both ample storage and advanced analytical capabilities. (shrink)

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 (...) key issue in effective execution of Cloud Computing is to adequately deal with the security in the cloud applications. This paper talks about the part of cryptography in cloud computing to improve the data security. The expectation here is to get bits of knowledge another security approach with the usage of cryptography to secure information at cloud data centers. (shrink)

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 (...) manner in the current methods for choosing cloud services. Hence, this study attempts to achieve this objective through construction. decision-making framework so-called cloud services evaluator (CSsEv). The main indicator and its sub-indicators are formed as nodes at levels(n) in tree soft sets (TSSs). Thereafter Single Value Neutrosophic Sets (SVNSs) as branch of neutrosophic sets which conjunction with the Multi-Criteria Decision Making (MCDM) technique to facilitate analysis and evaluation process for the available Cloud services providers. Hence, entropy is employed to obtain indicators and sub_indicators weights and Complex Proportional Assessment utilizes these weights to facilitate the decision process of selecting optimal ClSPs. (shrink)

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, (...) 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. (shrink)

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 (...) also further extends the basic reliability measures such as Mean Time Between Failure (MTBF), Mean Time To Repair (MTTR), Service Availability and Failure Rate, which measure system reliability and effectiveness. Moreover, the paper considers performance assessment methodologies through real-time monitoring, machine learning, and reliability assessment methods. It also addresses the nature and advancement of technologies of artificial intelligence-powered automation and self-healing applications for improved cloud dependability. The present work aims to identify the state-of-the-art state of dependability in cloud services and propose some recommendations for minimizing such costs, improving dependability levels, and reducing undesired downtime. The information is valuable for CSPs, IT designers/architects, and system engineers who wish to create fault-tolerant and optimal cloud environments. (shrink)

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 (...) operations for both astronauts and ground control teams. The paper discusses the challenges of operating in space environments, including latency, bandwidth limitations, and the need for secure data storage. We explore the integration of cloud platforms with space-based technologies such as satellites, rovers, and space stations, and analyze the future of cloud computing in advancing space exploration and interplanetary missions. Finally, we propose best practices for leveraging cloud technologies to enhance space missions and space-based research, improving collaboration, innovation, and operational efficiency. (shrink)

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 (...) Intelligence (AI). We discuss how cloud platforms support businesses in tracking and managing resource flows, implementing closed-loop systems, and optimizing product design, repair, and reuse. By analyzing real-world case studies from industries such as manufacturing, retail, and energy, we highlight the potential of cloud-based systems in driving sustainable business models that minimize waste and maximize resource recovery. The paper also addresses challenges in the integration of cloud computing with circular economy practices and provides insights into the future potential of cloud technologies in advancing sustainability. (shrink)

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.

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 (...) the carbon footprint of cloud computing and discusses emerging innovations such as green data centers, server optimization techniques, and the use of artificial intelligence (AI) for energy management. By highlighting case studies from leading companies, this paper presents a comprehensive approach to achieving sustainability in the cloud computing ecosystem. The paper concludes by emphasizing the importance of collaboration among industry stakeholders, policymakers, and consumers in accelerating the transition to net-zero emissions in the digital infrastructure sector. (shrink)

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 (...) to accommodate both individuals and organizations accessing applications and data in the cloud. While individual users may generate and share data, organizations often involve multiple users in data sharing to support their business processes. In these scenarios, multi-user data ownership and access management become critical, requiring secure sharing of cryptographic keys among the authorized users. To address these issues and ensure data confidentiality in multi-user cloud environments, the Improved Secure Cloud Data Storage Framework (ISCDSF) is introduced. This research not only enhances data security but also provides a comprehensive framework for secure data sharing in the cloud, catering to the needs of both individual users and organizations. (shrink)

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 (...) Pipeline, Azure Data Factory, Azure Synapse Studio, Google Cloud Dataflow, and Google Cloud Dataprep. The evaluation focuses on their respective features, integration capabilities, ease of use, and specific application scenarios, to aid organizations in selecting the most appropriate ETL tool based on their unique requirements and existing infrastructure. (shrink)

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 (...) studies from diverse industries, the study demonstrates how cloud-based HCM systems optimize talent acquisition, performance management, learning and development, and workforce analytics. Additionally, the research addresses the challenges associated with transitioning to cloud-based HCM solutions, including data security, privacy concerns, and change management. Best practices for implementing cloud architecture in HCM are discussed, emphasizing the importance of strategic planning, stakeholder engagement, and continuous evaluation. The findings underscore the pivotal role of cloud architecture in enhancing organizational efficiency, agility, and competitive advantage in today’s dynamic business environment. (shrink)

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 (...) core design principles for multi cloud data architectures and sheds light on problems in data fragmentation, latency, and security risks. It points to how Snowflake enables data resilience, including data replication, encryption, GDPR, and CCPA compliance. Details are provided. Practical implementation strategies of phased data migration ETL pipelines and integration with existing enterprise system to ensure a smooth deployment. Snowflake is seen as a clear win through a cost-benefit analysis with metrics like RTO and RPO that define how well Snowflake performs disaster recovery and business continuity. Additionally, the paper also looks at the emergence of tech like AI, blockchain and edge computing which could additionally bolster multi-cloud strategies even further. Finally, Snowflake enables the journey for P&C insurers through cloud ecosystem pitfalls, enabling operational resilience, regulatory compliance, along competitive advantage in a data-driven industry. (shrink)

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 (...) data analysis, self-optimizing cloud systems can automate routine tasks such as resource allocation, performance tuning, security management, and fault detection. This paper explores the concept of autonomous cloud operations, highlighting the role of AI and ML in enabling intelligent cloud systems that can autonomously adapt to changing workloads, optimize resource utilization, and improve overall system performance. It also discusses the benefits, challenges, and future prospects of autonomous cloud operations, providing insights into how these technologies can transform cloud management and operations. (shrink)

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, (...) the goal is to equip organizations with the necessary knowledge and insights to effectively leverage Azure networking for seamless cloud connectivity and enhanced security. (shrink)

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 (...) dangers to the data, reputation, and financial stability of enterprises. Conventional security methods can become inadequate when confronted with ever intricate and dynamic threats. Artificial Intelligence (AI) technologies possess the capacity to significantly transform cloud security through their ability to promptly identify and thwart assaults, adjust to emerging risks, and offer intelligent perspectives for proactive security actions. The objective of this research study is to investigate the utilization of AI technologies in augmenting the security measures within cloud computing systems. This paper aims to offer significant insights and recommendations for businesses seeking to protect their cloud-based assets by analyzing the present state of cloud security, the capabilities of AI, and the possible advantages and obstacles associated with using AI into cloud security policies. (shrink)

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 (...) made, like adding wearable device data in real-time or investigating deep learning techniques. (shrink)

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 (...) Data Security Contrivance to convert the cipher text using a secret-key block cipher of 64-bits. This system is designed to increase security and to improve the transmission performance. Storage-cheating attack model and Privacy-cheating attack model are implemented to protect the data on cloud. Findings: This system increases security and improves transmission performance. The blowfish algorithm is secure against unauthorized attacks and runs faster than the popular existing algorithms. Storage-cheating attack model and Privacy-cheating attack model provides the data confidentiality for data stored in the cloud in higher way. Improvements: The system can be implemented in real cloud system in the future. (shrink)

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 (...) class='Hi'>cloud 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)

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 (...) network traffic, detect anomalies, and identify advanced cyber threats with high accuracy. Unlike rule-based IDS, which rely on static signatures, our model continuously learns from real-time data, improving detection rates while reducing false alarms. The proposed AI-IDS is optimized for cloud infrastructure, ensuring low-latency threat detection, minimal computational burden, and real-time adaptability to emerging attack patterns. Experimental validation on benchmark datasets demonstrates significant improvements in accuracy, precision, and scalability, making AI-powered IDS a crucial innovation in cloud security. (shrink)

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 (...) Data Security Contrivance to convert the cipher text using a secret-key block cipher of 64-bits. This system is designed to increase security and to improve the transmission performance. Storage-cheating attack model and Privacy-cheating attack model are implemented to protect the data on cloud. Findings: This system increases security and improves transmission performance. The blowfish algorithm is secure against unauthorized attacks and runs faster than the popular existing algorithms. Storage-cheating attack model and Privacy-cheating attack model provides the data confidentiality for data stored in the cloud in higher way. Improvements: The system can be implemented in real cloud system in the future. (shrink)

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.

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 (...) applications and resources are processed at the edge of the cloud, rather than processing entire applications on the cloud. (shrink)

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 (...) traceability. This study concludes with an evaluation of the deduplication framework's impact on cost efficiency, system performance, and potential scalability. Future enhancements aim to integrate multi-cloud interoperability and advanced compression algorithms to further refine storage management. (shrink)