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1
KashifMunir, and Lawan A. Mohammed. "AUTHENTICATION SCHEME FOR DATABASE AS A SERVICE(DBAAS)." International Journal on Cloud Computing: Services and Architecture (IJCCSA) 8, no. 1/2/3/4/5 (2018): 01–12. https://doi.org/10.5281/zenodo.1489022.
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IT Companies have shifted their resources to the cloud at rapidly increasing rate. As part of this trend companies are migrating business critical and sensitive data stored in database to cloud-hosted and Database as a Service (DBaaS) solutions.Of all that has been written about cloud computing, precious little attention has been paid to authentication in the cloud. In this paper we have designed a new effective authentication scheme for Cloud Database as a Service (DBaaS). A user can change his/her password, whenever demanded. Furthermore, security analysis realizes the feasibility of the proposed model for DBaaS and achieves efficiency. We also proposed an efficient authentication scheme to solve the authentication problem in cloud. The proposed solution which we have provided is based mainly on improved Needham-Schroeder’s protocol to prove the users’ identity to determine if this user is authorized or not. The results showed that this scheme is very strong and difficult to break it.
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KashifMunir, and Lawan A. Mohammed. "AUTHENTICATION SCHEME FOR DATABASE AS A SERVICE(DBAAS)." International Journal on Cloud Computing: Services and Architecture (IJCCSA) 8, no. 1/2/3/4/5 (2023): 11. https://doi.org/10.5281/zenodo.7551252.
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IT Companies have shifted their resources to the cloud at rapidly increasing rate. As part of this trend companies are migrating business critical and sensitive data stored in database to cloud-hosted and Database as a Service (DBaaS) solutions.Of all that has been written about cloud computing, precious little attention has been paid to authentication in the cloud. In this paper we have designed a new effective authentication scheme for Cloud Database as a Service (DBaaS). A user can change his/her password, whenever demanded. Furthermore, security analysis realizes the feasibility of the proposed model for DBaaS and achieves efficiency. We also proposed an efficient authentication scheme to solve the authentication problem in cloud. The proposed solution which we have provided is based mainly on improved Needham-Schroeder’s protocol to prove the users’ identity to determine if this user is authorized or not. The results showed that this scheme is very strong and difficult to break it.
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Suruchi, Shah. "A REVIEW ON DATABASE SECURITY CHALLENGES IN CLOUD COMPUTING ENVIRONMENT." International Journal of Computer Engineering and Technology (IJCET) 15, no. 5 (2024): 842–52. https://doi.org/10.5281/zenodo.13922361.
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Cloud computing is a system that offers many resources that may be customized, allowing for decentralized data management and storage. Cloud technologies have revolutionized concepts of data storage and access in organizations thus offering organizations flexible and efficient solutions. Cloud services such as DBaaS allows user to utilize sophisticated capabilities of databases without the responsibility of conventional databases. But with cloud computing, there is a great concern of security since issues such as data privacy, access control and compliance to regulatory requirements are paramount. This paper also explores the cloud computing architectural model, the differences between DBaaS and conventional cloud offerings, and the security risks of DBaaS. Much as it discusses the key areas of database security like data confidentiality, data integrity, and data availability, it provides information on security threats like the SQL injection or data breaches. Besides, it provides guidance on vulnerability management and incident handling in a context of cloud computing. To this end, this paper focuses on the conceptual clarification of the cloud database security best practices and the shared responsibility model between the providers and the users.
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Munir, Kashif, and Lawan A. Mohammed. "Authentication Scheme for Database as a Service (DBAAS) Solutions." International Journal on Cloud Computing: Services and Architecture 8, no. 1/2/3/4/5 (2018): 11–22. http://dx.doi.org/10.5121/ijccsa.2018.8502.
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Estrela, Vania V. "Biomedical Cyber-Physical Systems in the Light of Database as a Service (DBaaS) Paradigm." Medical Technologies Journal 4, no. 3 (2020): 577. http://dx.doi.org/10.26415/2572-004x-vol4iss3p577-577.
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Background: A database (DB) to store indexed information about drug delivery, test, and their temporal behavior is paramount in new Biomedical Cyber-Physical Systems (BCPSs). The term Database as a Service (DBaaS) means that a corporation delivers the hardware, software, and other infrastructure required by companies to operate their databases according to their demands instead of keeping an internal data warehouse.
 Methods: BCPSs attributes are presented and discussed. One needs to retrieve detailed knowledge reliably to make adequate healthcare treatment decisions. Furthermore, these DBs store, organize, manipulate, and retrieve the necessary data from an ocean of Big Data (BD) associated processes. There are Search Query Language (SQL), and NoSQL DBs. 
 Results: This work investigates how to retrieve biomedical-related knowledge reliably to make adequate healthcare treatment decisions. Furthermore, Biomedical DBaaSs store, organize, manipulate, and retrieve the necessary data from an ocean of Big Data (BD) associated processes.
 Conclusion: A NoSQL DB allows more flexibility with changes while the BCPSs are running, which allows for queries and data handling according to the context and situation. A DBaaS must be adaptive and permit the DB management within an extensive variety of distinctive sources, modalities, dimensionalities, and data handling according to conventional ways.
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König, Arnd Christian, Yi Shan, Karan Newatia, Luke Marshall, and Vivek Narasayya. "Solver-In-The-Loop Cluster Resource Management for Database-as-a-Service." Proceedings of the VLDB Endowment 16, no. 13 (2023): 4254–67. http://dx.doi.org/10.14778/3625054.3625062.
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In Database-as-a-Service (DBaaS) clusters, resource management is a complex optimization problem that assigns tenants to nodes, subject to various constraints and objectives. Tenants share resources within a node, however, their resource demands can change over time and exhibit high variance. As tenants may accumulate large state, moving them to a different node becomes disruptive, making intelligent placement decisions crucial to avoid service disruption. Placement decisions need to account for dynamic changes in tenant resource demands, different causes of service disruption, and various placement constraints, giving rise to a complex search space. In this paper, we show how to bring combinatorial solvers to bear on this problem, formulating the objective of minimizing service disruption as an optimization problem amenable to fast solutions. We implemented our approach in the Service Fabric cluster manager codebase. Experiments show significant reductions in constraint violations and tenant moves, compared to the previous state-of-the-art, including the unmodified Service Fabric cluster manager, as well as recent research on DBaaS tenant placement.
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Vieira, Marcelo Aires, Elivaldo Lozer Fracalossi Ribeiro, Daniela Barreiro Claro, and Babacar Mane. "Integration Model between Heterogeneous Data Services in a Cloud." JUCS - Journal of Universal Computer Science 27, no. 4 (2021): 387–412. http://dx.doi.org/10.3897/jucs.67046.
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With the growth of cloud services, many companies have begun to persist and make their data available through services such as Data as a Service (DaaS) and Database as a Service (DBaaS). The DaaS model provides on-demand data through an Application Programming Inter- face (API), while DBaaS model provides on-demand database management systems. Different data sources require efforts to integrate data from different models. These model types include unstructured, semi-structured, and structured data. Heterogeneity from DaaS and DBaaS makes it challenging to integrate data from different services. In response to this problem, we developed the Data Join (DJ) method to integrate heterogeneous DaaS and DBaaS sources. DJ was described through canonical models and incorporated into a middleware as a proof-of-concept. A test case and three experiments were performed to validate our DJ method: the first experiment tackles data from DaaS and DBaaS in isolation; the second experiment associates data from different DaaS and DBaaS through one join clause; and the third experiment integrates data from three sources (one DaaS and two DBaaS) based on different data type (relational, NoSQL, and NewSQL) through two join clauses. Our experiments evaluated the viability, functionality, integration, and performance of the DJ method. Results demonstrate that DJ method outperforms most of the related work on selecting and integrating data in a cloud environment.
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Vieira, Marcelo Aires, Elivaldo Lozer Fracalossi Ribeiro, Daniela Barreiro Claro, and Babacar Mane. "Integration Model between Heterogeneous Data Services in a Cloud." JUCS - Journal of Universal Computer Science 27, no. (4) (2021): 387–412. https://doi.org/10.3897/jucs.67046.
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With the growth of cloud services, many companies have begun to persist and make their data available through services such as Data as a Service (DaaS) and Database as a Service (DBaaS). The DaaS model provides on-demand data through an Application Programming Inter- face (API), while DBaaS model provides on-demand database management systems. Different data sources require efforts to integrate data from different models. These model types include unstructured, semi-structured, and structured data. Heterogeneity from DaaS and DBaaS makes it challenging to integrate data from different services. In response to this problem, we developed the Data Join (DJ) method to integrate heterogeneous DaaS and DBaaS sources. DJ was described through canonical models and incorporated into a middleware as a proof-of-concept. A test case and three experiments were performed to validate our DJ method: the first experiment tackles data from DaaS and DBaaS in isolation; the second experiment associates data from different DaaS and DBaaS through one join clause; and the third experiment integrates data from three sources (one DaaS and two DBaaS) based on different data type (relational, NoSQL, and NewSQL) through two join clauses. Our experiments evaluated the viability, functionality, integration, and performance of the DJ method. Results demonstrate that DJ method outperforms most of the related work on selecting and integrating data in a cloud environment.
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Da Silveira Segalin, Vinicius, Carina Friedrich Dorneles, and Mario Antonio Ribeiro Dantas. "DBaaS Multitenancy, Auto-tuning and SLA Maintenance in Cloud Environments: a Brief Survey." iSys - Brazilian Journal of Information Systems 11, no. 2 (2018): 30–42. http://dx.doi.org/10.5753/isys.2018.362.
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Cloud computing is a paradigm that presents many advantages to both costumers and service providers, such as low upfront investment, pay-per-use and easiness of use, delivering/enabling scalable services using Internet technologies. Among many types of services we have today, Database as a Service (DBaaS) is the one where a database is provided in the cloud in all its aspects. Examples of aspects related to DBaaS utilization are data storage, resources management and SLA maintenance. In this context, an important feature, related to it, is resource management and performance, which can be done in many different ways for several reasons, such as saving money, time, and meeting the requirements agreed between client and provider, that are defined in the Service Level Agreement (SLA). A SLA usually tries to protect the costumer from not receiving the contracted service and to ensure that the provider reaches the profit intended. In this paper it is presented a classification based on three main parameters that aim to manage resources for enhancing the performance on DBaaS and guarantee that the SLA is respected for both user and provider sides benefit. The proposal is based upon a survey of existing research work efforts.
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Ferrari, Paolo, Emiliano Sisinni, Alessandro Depari, et al. "On the Performance of Cloud Services and Databases for Industrial IoT Scalable Applications." Electronics 9, no. 9 (2020): 1435. http://dx.doi.org/10.3390/electronics9091435.
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In the Industry 4.0 the communication infrastructure is derived from the Internet of Things (IoT), and it is called Industrial IoT or IIoT. Smart objects deployed on the field collect a large amount of data which is stored and processed in the Cloud to create innovative services. However, differently from most of the consumer applications, the industrial scenario is generally constrained by time-related requirements and its needs for real-time behavior (i.e., bounded and possibly short delays). Unfortunately, timeliness is generally ignored by traditional service provider, and the Cloud is treated as a black box. For instance, Cloud databases (generally seen as “Database as a service”—DBaaS) have unknown or hard-to-compare impact on applications. The novelty of this work is to provide an experimental measurement methodology based on an abstract view of IIoT applications, in order to define some easy-to-evaluate metrics focused on DBaaS latency (no matter the actual implementation details are). In particular, the focus is on the impact of DBaaS on the overall communication delays in a typical IIoT scalable context (i.e., from the field to the Cloud and the way back). In order to show the effectiveness of the proposed approach, a real use case is discussed (it is a predictive maintenance application with a Siemens S7 industrial controller transmitting system health status information to a Cloudant DB inside the IBM Bluemix platform). Experiments carried on in this use case provide useful insights about the DBaaS performance: evaluation of delays, effects of involved number of devices (scalability and complexity), constraints of the architecture, and clear information for comparing with other implementations and for optimizing configuration. In other words, the proposed evaluation strategy helps in finding out the peculiarities of Cloud Database service implementations.
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Gahi, Youssef, Imane El Alaoui, and Mouhcine Guennoun. "An End to End Cloud Computing Privacy Framework Using Blind Processing." International Journal of Smart Security Technologies 7, no. 1 (2020): 1–20. http://dx.doi.org/10.4018/ijsst.2020010101.
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Database-as-a-service (DBaaS) is a trend allowing organizations to outsource their databases and computations to external parties. However, despite the many advantages provided by this service in terms of cost reduction and efficiency, DBaaS raises many security issues regarding data privacy and access control. The protection of privacy has been addressed by several research contributions proposing efficient solutions such as encrypted databases and blind queries over encrypted data, called blind processing. In this latter context, almost all proposed schemes consider an architecture of a single user (the data owner) that requests the database server for encrypted records while he is the only one capable of decrypting. From a practical perspective, a database system is set up to support not only a single user but multiple users initiating multiple queries. However, managing various accesses to an encrypted database introduces several challenges by itself, like key sharing, key revocation, and data re-encryption. In this article, we propose a simple and efficient blind processing protocol that allows multiple users to query the same encrypted data and decrypt the retrieved results without getting access to the secret key.
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Alzoubaidi, Abdel Rahman. "Private Cloud Computing Services for an Interactive Multi-Campus University." International Journal of Interactive Mobile Technologies (iJIM) 10, no. 4 (2016): 37. http://dx.doi.org/10.3991/ijim.v10i4.5931.
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<span>Cloud Computing is an environment where computing resources, such as processing power, storage, network, application, and other IT services, are provided to users as computing utility. This paper presents the university distributed databases consolidation and relocation to the cloud for the provision of Database as a Service (DBaaS), through their deployment into high availability, interactive, secure private cloud setup utilizing Al-Balqa Applied University (BAU) Private Cloud (BPC). This solution involves several transitions, and represents the main key step in BAU journey to the cloud to allow the university to achieve greater efficiency in terms of database services, and to improve performance, availability, interactivity, and security. The resulted service also reduces operating, management and capital costs.</span>
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Rabelo Ferreira, Fred Eduardo Revoredo, and Robson do Nascimento Fidalgo. "A Performance Analysis of Hybrid and Columnar Cloud Databases for Efficient Schema Design in Distributed Data Warehouse as a Service." Data 9, no. 8 (2024): 99. http://dx.doi.org/10.3390/data9080099.
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A Data Warehouse (DW) is a centralized database that stores large volumes of historical data for analysis and reporting. In a world where enterprise data grows exponentially, new architectures are being investigated to overcome the deficiencies of traditional Database Management Systems (DBMSs), driving a shift towards more modern, cloud-based solutions that provide resources such as distributed processing, columnar storage, and horizontal scalability without the overhead of physical hardware management, i.e., a Database as a Service (DBaaS). Choosing the appropriate class of DBMS is a critical decision for organizations, and there are important differences that impact data volume and query performance (e.g., architecture, data models, and storage) to support analytics in a distributed cloud environment efficiently. In this sense, we carry out an experimental evaluation to analyze the performance of several DBaaS and the impact of data modeling, specifically the usage of a partially normalized Star Schema and a fully denormalized Flat Table Schema, to further comprehend their behavior in different configurations and designs in terms of data schema, storage form, memory availability, and cluster size. The analysis is done in two volumes of data generated by a well-established benchmark, comparing the performance of the DW in terms of average execution time, memory usage, data volume, and loading time. Our results provide guidelines for efficient DW design, showing, for example, that the denormalization of the schema does not guarantee improved performance, as solutions performed differently depending on its architecture. We also show that a Hybrid Processing (HTAP) NewSQL solution can outperform solutions that support only Online Analytical Processing (OLAP) in terms of overall execution time, but that the performance of each query is deeply influenced by its selectivity and by the number of join functions.
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Li, Guoliang, Haowen Dong, and Chao Zhang. "Cloud databases." Proceedings of the VLDB Endowment 15, no. 12 (2022): 3758–61. http://dx.doi.org/10.14778/3554821.3554893.
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As database vendors are increasingly moving towards the cloud data service, i.e., databases as a service (DBaaS), cloud databases have become prevalent. Compared with the early cloud-hosted databases, the new generation of cloud databases, also known as cloud-native databases, seek for higher elasticity and lower cost by developing new techniques, e.g., compute-storage disaggregation and the log is the database. To better harness the power of these cloud databases, it is important to study and compare the pros and cons of their key techniques. In this tutorial, we offer a comprehensive survey of cloud-native databases. Based on various system architectures, we introduce a taxonomy for the state-of-the-art cloud-native OLTP databases and OLAP databases, respectively. We then take a deep dive into their key techniques regarding storage management, transaction processing, analytical processing, data replication, serverless computing, database recovery, and security. Finally, we discuss the research challenges and opportunities.
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Sai Venkata Kondapalli. "Cloud Database Scalability: Meeting Modern Enterprise Demands." World Journal of Advanced Engineering Technology and Sciences 15, no. 1 (2025): 2278–90. https://doi.org/10.30574/wjaets.2025.15.1.0469.
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Cloud database technologies have emerged as a critical solution for enterprises grappling with explosive data growth and unpredictable workload patterns. This comprehensive article examines how modern cloud database systems address enterprise scalability challenges through dynamic resource allocation, distributed architectures, and automated management capabilities. Further, we deep dive into the core scalability technologies, including horizontal and vertical scaling approaches, automatic scaling mechanisms, and distributed database architectures that enable organizations to handle exponentially growing datasets. The article further analyzes various database service models (DBaaS, cloud-native distributed databases, self-managed deployments), resource optimization strategies (connection pooling, query optimization, workload management), and crucial implementation considerations for successful cloud database migrations. Through real-world examples across industries, this article demonstrates how properly implementing these technologies allows enterprises to balance performance requirements with cost optimization while maintaining the business agility required in today's data-driven landscape.
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Yan, Baoyue, Xuntao Cheng, Bo Jiang, et al. "Revisiting the design of LSM-tree Based OLTP storage engine with persistent memory." Proceedings of the VLDB Endowment 14, no. 10 (2021): 1872–85. http://dx.doi.org/10.14778/3467861.3467875.
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The recent byte-addressable and large-capacity commercialized persistent memory (PM) is promising to drive database as a service (DBaaS) into unchartered territories. This paper investigates how to leverage PMs to revisit the conventional LSM-tree based OLTP storage engines designed for DRAM-SSD hierarchy for DBaaS instances. Specifically we (1) propose a light-weight PM allocator named Hal-loc customized for LSM-tree, (2) build a high-performance Semi-persistent Memtable utilizing the persistent in-memory writes of PM, (3) design a concurrent commit algorithm named Reorder Ring to aschieve log-free transaction processing for OLTP workloads and (4) present a Global Index as the new globally sorted persistent level with non-blocking in-memory compaction. The design of Reorder Ring and Semi-persistent Memtable achieves fast writes without synchronized logging overheads and achieves near instant recovery time. Moreover, the design of Semi-persistent Memtable and Global Index with in-memory compaction enables the byte-addressable persistent levels in PM, which significantly reduces the read and write amplification as well as the background compaction overheads. The overall evaluation shows that the performance of our proposal over PM-SSD hierarchy outperforms the baseline by up to 3.8x in YCSB benchmark and by 2x in TPC-C benchmark.
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Kazheen, S. . Muhammad, and Maseeh Yasin Hajar. "Scalable Database Solutions in the Cloud Era: Challenges and Best Practices." Engineering and Technology Journal 10, no. 05 (2025): 5192–204. https://doi.org/10.5281/zenodo.15532508.
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Cloud computing has revolutionized data management, creating demand for highly scalable and adaptive database systems. Traditional architecture has given way to cloud-native databases that offer elasticity, modularity, and real-time responsiveness. This paper reviews modern approaches to building scalable cloud databases, highlighting critical challenges and emerging solutions. Key advancements include microservices-based architecture and intelligent tuning systems like CDBTune and HUNTER, which use AI to optimize performance under dynamic workloads. Security is addressed through homomorphic encryption, blockchain, and oblivious data structures, ensuring data protection in untrusted environments. The study also examines migration strategies and middleware for cross-platform interoperability between SQL and NoSQL systems. Application use cases across agriculture, IoT, healthcare, and industrial domains illustrate practical impacts. Benchmarking approaches focus on latency, throughput, and cost-efficiency. By analyzing over 40 research sources, this paper provides actionable best practices for designing resilient, secure, and efficient cloud database solutions that meet the demands of today’s data-intensive world.
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P., Raviteja, Kumar M.Uday, Parimala M., and Someswar G.Manoj. "PERFORMANCE AND COST EVALUATION OF AN ADAPTIVE ENCRYPTION ARCHITECTURE FOR CLOUD DATABASES." COMPUSOFT: An International Journal of Advanced Computer Technology 05, no. 06 (2016): 2149–55. https://doi.org/10.5281/zenodo.14799172.
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The cloud computing paradigm is successfully converging as the fifth utility, but this positive trend is partially limited by concerns about information confidentiality and unclear costs over a medium-long term. We are interested in the Database as a Service paradigm (DBaaS) that poses several research challenges in terms of security and cost evaluation from a tenant"s point of view. Most results concerning encryption for cloud-based services are inapplicable to the database paradigm. Other encryption schemes, which allow the execution of SQL operations over encrypted data, either suffer from performance limits or they require the choice of which encryption scheme must be adopted for each database column and SQL operations. These latter proposals are fine when the set of queries can be statically determined at design time, while in this paper we are interested to other common scenarios where the workload may change after the database design. In this system, we propose a novel architecture for adaptive encryption of public cloud databases that offers a proxy-free alternative to the system proposed in. The proposed architecture guarantees in an adaptive way the best level of data confidentiality for any database workload, even when the set of SQL queries dynamically changes. The adaptive encryption scheme, which was initially proposed for applications not referring to the cloud, encrypts each plain column into multiple encrypted columns, and each value is encapsulated into different layers of encryption, so that the outer layers guarantee higher confidentiality but support fewer computation capabilities with respect to the inner layers. The outer layers are dynamically adapted at runtime when new SQL operations are added to the workload.
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Banothu, Srinu, Janardhan G, Sirisha G, Srinivasulu Shepuri, Madhavi Karnam, and Balaram Allam. "A Secure Data Storage Approach for Online Examination Platform using Cloud DBAAS Service." Scalable Computing: Practice and Experience 25, no. 5 (2024): 3715–24. http://dx.doi.org/10.12694/scpe.v25i5.3113.
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For the time being, many government or private organizations for recruitment of staff or educational institutions moving towards online based tests. The online examination system is a software application used for conducting examination using computer systems. It helps to the recruitment agency or any govt. or private organizations for conducting any job recruitment examinations transparently. Due to this system results are processed without delay and efficiently evaluated to assess the candidate’s abilities. But the biggest challenge for online examination system is data integrity, security and privacy. The current system is resolving the privacy issue by providing authentication credentials such as user name, password to the candidates. So that only authorized users with proper credentials can login to the system and attempt the exam. But the data confidentiality and integrity are biggest challenges for the system. As the data stored in system database is in plain text format, hence it may be modified or misused by the internal staff of the organization. This paper presents the frame work for secure storage and management of candidate’s data using encryption scheme, distributed databases in cloud database system. The proposed framework enhances the data confidentiality, integrity and avoids any cheating by internal staff or third party institutions. This paper conducts experimental work on proposed framework and analyses the results of the system.
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Desai, Janvi. "Self-Optimizing Database Architecture." International Journal for Research in Applied Science and Engineering Technology 9, no. 11 (2021): 1675–78. http://dx.doi.org/10.22214/ijraset.2021.39071.
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Abstract: Over the most recent decades, analysts and database service providers have fabricated devices to help DBAs (Database Administrators) in various parts of framework tuning and the actual design of the database. Most of this past work, regardless, is fragmented on the grounds that it expects people to come up with an official agreement or judgement about any modifications to the data in the database and fix issues after they happen rather than preventing such cases from taking place or adjusting to these changes automatically. What is required for a really "self-driving" database management system (DBMS) is another way of approaching this that is intended for independent activity and automatic decision making. This is different from prior endeavors since all angles of this framework are constrained by a coordinated arranging part that not just enhance the framework for the current responsibility, but in addition to this, it also predicts future responsibility that might take place and prepares itself for such not-so-common occurrences and adjusts to them as required while keeping the efficiency of the operations as close to normal as possible. With this, the DBMS can uphold all the past tuning procedures without requiring a human to decide the right way and proper opportunity to use them. It likewise empowers new advancements that are significant for current DBMSs (Database Management System), which are impractical today because of the fact that the intricacy of overseeing these frameworks has outperformed the abilities of human specialists who are supposed to tune them and make changes when required. Keywords: Database Management System, Database Administrator, Forecasting, Long Short-Term Memory, Recurrent Neural Networks
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Mr.Satish.C.Cholke and Prof.S.B.Natikar. "NEW SECURE CONCURRECY MANEGMENT APPROACH FOR DISTRIBUTED AND CONCURRENT ACCESS OF ENCRYPTED CLOUD DATABASES USING DBAAS." IJIERT - International Journal of Innovations in Engineering Research and Technology ICITDCEME-15 (December 20, 2015). https://doi.org/10.5281/zenodo.1473219.
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<strong>Handover the critical data to the cloud provider sh ould have the guarantee of security and availabilit y for data at rest,in motion,and in use. Many alternatives sys tems exist for storage services,but the data confi dentiality in the database as a service paradigm are still immature. We propose a novel architecture that integrates clo ud database services paradigm with data confidentiality and exe cuting concurrent operations on encrypted data. Thi s is the method supporting geographically distributed client s to connect directly and access to an encrypted cl oud database,and to execute concurrent and independent operation s by using modifying the database structure. The proposed architecture has also the more advanta ge of removing intermediate proxies that limit the flexibility,availability,and expandability properties that are inbuilt in cloud-based systems. The efficacy of th e proposed architecture is evaluated by theoretical analyses a nd extensive experimental results with the help of prototype implementation related to the TPC-C standard benchm ark for various categories of clients and network l atencies. We propose a multi-keyword ranked search method for the encrypted cloud data databases,which simultan eously fulfill the needs of privacy requirements. The prop osed scheme could return not only the exact matchin g files,but also the files including the terms latent semantica lly associated to the query keyword.</strong> https://www.ijiert.org/paper-details?paper_id=140375
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Ferrari, Paolo, Emiliano Sisinni, Alessandro Depari, et al. "On the Performance of Cloud Services and Databases for Industrial IoT Scalable Applications." September 3, 2020. https://doi.org/10.3390/electronics9091435.
Full textAbstract:
In the Industry 4.0 the communication infrastructure is derived from the Internet of Things (IoT), and it is called Industrial IoT or IIoT. Smart objects deployed on the field collect a large amount of data which is stored and processed in the Cloud to create innovative services. However, differently from most of the consumer applications, the industrial scenario is generally constrained by time-related requirements and its needs for real-time behavior (i.e., bounded and possibly short delays). Unfortunately, timeliness is generally ignored by traditional service provider, and the Cloud is treated as a black box. For instance, Cloud databases (generally seen as "Database as a service"—DBaaS) have unknown or hard-to-compare impact on applications. The novelty of this work is to provide an experimental measurement methodology based on an abstract view of IIoT applications, in order to define some easy-to-evaluate metrics focused on DBaaS latency (no matter the actual implementation details are). In particular, the focus is on the impact of DBaaS on the overall communication delays in a typical IIoT scalable context (i.e., from the field to the Cloud and the way back). In order to show the effectiveness of the proposed approach, a real use case is discussed (it is a predictive maintenance application with a Siemens S7 industrial controller transmitting system health status information to a Cloudant DB inside the IBM Bluemix platform). Experiments carried on in this use case provide useful insights about the DBaaS performance: evaluation of delays, effects of involved number of devices (scalability and complexity), constraints of the architecture, and clear information for comparing with other implementations and for optimizing configuration. In other words, the proposed evaluation strategy helps in finding out the peculiarities of Cloud Database service implementations.
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"Data Security for Outsourced Cloud Datausing HASBE Scheme and RSA Algorithm." International Journal of Innovative Technology and Exploring Engineering 8, no. 12S (2019): 705–8. http://dx.doi.org/10.35940/ijitee.l1167.10812s19.
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Cloud computing (CC) is the expertise over which every person is capable of sharing the reserves, amenities, and evidence amongst the individuals as a result of harnessing the internet in link. Subsequently, protection is a key concern on the facts pooled by means of the internet. In CC a numerous security issues prone to occur that includes confidentiality, integrity, authentication and/or thin well-honed edit control (TWHEC). In this research an innovative security replica has been aforethought. The design stipulates an approach across which secure communication besides data hiding from unauthorized punters can be got hold of. The security resolved with all categories of CC aspects similar to Platform as a Service (aaS), and Process aaS (PaaS), Software aaS, Storage aaS and Security aaS (SaaS), Network aaS (NaaS), Functions aaS (FaaS), Infrastructure aaS, Information aaS, and Integration aaS (IaaS), Database aaS (DBaaS), Application as a Service aaS and API aaS (AaaS), Management aaS (MaaS), Testing aaS (TaaS), etc., This anticipated system yield thin well-honed, mutable and ascendable statistics editing control by means of the manipulation of complex traits of Hierarchical (Ranked/Ordered) attribute-set-based encryption (HASBE). This multifarious qualities of blend of HASBE and Rivest–Shamir–Adleman (RSA) algorithm too. For instance, cyber individual healthiness record (IHR) aids sick persons to deal with his/her personal medicinal archives into a unified means that is to a great extent vital in storing, editing and partaking of the individual healthiness data. Further down encryption, it is impeding in accomplishing the TWHEC to CIHR data in an ascendable and effectual technique by using HASBE. Prevailing RSA encryption does not endow the data with high security in health. To fulfill ascendable, elastic, and thin well-honed edit control of subcontracted statistics in cloud. In this archetypal instigated a mish-mash RSA encryption with HASBE. Cyber IHR dispenses with patients to get along medical archives in a secure way, in which very significant concerns are the storing, access and distribution of individual wellness information. This composite process is responsible for three mode precautions, i.e. data precautions, certification and corroboration. In this report, the HASBE encryption algorithm has been put forward in realizing TWHEC to IHR data in an ascendable and effectual way
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Liao, Weidong, Annus Ashiq, and Osman Guzide. "System Administration and Database Administration in Cloud Computing Era." Proceedings of the West Virginia Academy of Science 91, no. 1 (2019). http://dx.doi.org/10.55632/pwvas.v91i1.506.
Full textAbstract:
The ever-changing nature of IT demands a changing role for both system administrators and database administrators. Being system admin personnel will require more knowledge, broader skillset, and more tools on hand to be able to adapt to the cloud computing culture. The cloud computing has changed the way for IT Operations. The future system administrator will thus have to help configure, implement and manage the applications that run on cloud platforms. The same thing happens to database administrators as well. The role of DBAs will shift to cloud DBAs, and adding to their responsibilities will manage the cloud based database and NoSQL databases in serverless settings. Cloud DBAs will have to deal with data protection and play a key role in providing data compatibility across the cloud platforms and maybe migrating data storage from one cloud service provider to another. In short DBAs role moved from tactical infrastructure caretakers towards a more strategic role of being an advisor for other developers. In this poster, we describe changes of roles of system administrators and database administrators in the era of cloud computing.