Cloud Data Storage Research Articles

Securing the Cloud: A New Horizon of Hybrid Automated System for Storage Protection

While cloud storage seems dependable and scalable, the necessity for it is increasing every day. The intricacies involved in securing data in terms of privacy and confidentiality makes the storing and administration of user information at a remote location problematic. The cloud third party who is in charge of handling the issues concerned with data security present within the cloud systems could end up being an unreliable insider. In order to enhance the protection of data and ensure the confidentiality of information without any sort of interruption from cloud third parties, the current research provides an automated hybrid Cryptographic algorithm for Cloud Data Storage. Improved automated Asynchronous Encryption for Data Streams (AEDS) and enhanced automated Concurrent Encryption for Data Blocks (CEDB) are two encryption techniques that are used to achieve great performance and efficiency. We introduce a unique encryption method in Enhanced Automated Concurrent Encryption by transforming the fixed S-box in the conventional AES to a varying S-box utilising a Ternary Galois field and Complementary Ternary Galois field in the proposed work. Additionally, the Ternary Galois field and Complementary Ternary Galois field are employed to transform the matrix used for the AES mix column technique into a dynamic matrix.

Research on Edge Cloud Data Storage Method of Power Operation Site in Internet of Things Environment Based on Paxos Algorithm

Abstract In order to realize the efficient storage of electric power job site data and ensure the utilization effect of the stored data, a method of electric power job site edge cloud data storage based on the Paxos algorithm is proposed. In this method, power field operation data are collected comprehensively through the edge server and edge controller in the edge computing module, the collected data are processed, and the data storage tasks are allocated reasonably. The allocated data are transferred to the data storage module, which identifies the bad data in the data through a gap statistics algorithm and cluster analysis and retains the valid and normal data. After the primary and secondary nodes are determined based on the Paxos algorithm, the data storage model of power operation site is constructed. After the consistency detection of the reserved data, the data storage of power operation site is completed. The platform management module can analyze the stored data and present the analysis results to the application decision-making module for presentation. The test results show that the maximum time delay and energy consumption are 2.15 s and 42.6 W, respectively, when the method is used for data transmission, which can accurately identify the bad data in the field data of electric power operation, and the reliability index results of data consistency detection are all above 0.95, which ensures the good consistency of the stored power operation site data and effectively completes the power operation site data storage.

A Kotlin and Firebase Based Project Discovery Platform with Cosine Similarity-Based Recommendation

Abstract: In today's interconnected world, mobile applications have become integral to our daily lives, revolutionizing how we communicate, work, and collaborate. we present an Android application utilizing Kotlin, Firebase, and a cosine-based recommendation system to address the challenge of project collaboration and discovery. The application aims to provide users with a seamless and personalized experience, empowering them to discover, collaborate on, and contribute to projects aligned with their interests and expertise. By integrating Firebase, the application ensures real-time data synchronization, secure authentication, and cloud storage capabilities, enhancing user experience. The implementation of a cosine-based recommendation system further enhances project discovery by analyzing user profiles and project data to generate personalized recommendations. This paper offers insights into the architecture, methodology, and implementation details of the Android application, highlighting its innovative features and technologies for collaborative project management.

Modern possibilities of functional glaucoma screening (part 2)

Nowadays methods of standard and non-standard computerized perimetry using stationary devices are widely used in functional screening of glaucoma. The information about new portable devices for perimetry has appeared in foreign literature in recent years, describing such advantages as economic availability, autonomy and mobility, which open up new possibilities for their use. New possibilities include cloud storage of data, the use of telemedicine technologies, artificial intelligence, examination of patients with disabilities, including those who are bedridden, as well as examination outside of medical institutions. All of this can allow glaucoma patients to receive ophthalmic care when in-person visits are unavailable, including social distancing needed during a pandemic or quarantine. This review of the literature describes the latest portable devices and applications for perimetry, attempts to classify them according to similar parameters, and assesses their advantages and disadvantages, as well as the prospects for their use in functional screening of glaucoma.

INTERFACES OF VIRTUAL DATA STORAGE IN THE CONDITIONS OF A FAST-CHANGING INFORMATION ENVIRONMENT

The article analyzes data storage architectures, explores the main approaches to cloud technologies, and highlights the features of virtual data storage architecture formation. In the process of analysis, positive and negative features of individual data storage architectures were highlighted. Cloud information technologies are considered from the point of view of their use for data storage and distribution. When considering cloud data storage, attention is focused on their architectural features from the point of view of efficiency and availability for users. Storage efficiency is an important characteristic of cloud storage infrastructure, especially given its emphasis on overall cost savings. Performance has many aspects, but the main task of a cloud storage system is to move data between the user and the remote cloud service provider. The system architecture was designed based on the proposed and modeled methods of organizing access to the cloud storage. According to the designed architecture, the data flows in the system were analyzed and investigated. The developed algorithm for the collection and integration of disparate data based on virtual data warehouses, in contrast to the Inmon and Kimball models, makes it possible to process NoSQL temporal (InfluxDB), graph (Neo4j) and document-oriented (MongoDB) data with a significantly lower value of capacity complexity and the possibility execution of recursive queries. The developed interface should be able to work with relational, temporal, graph and document-oriented data sources. To do this, it must provide the ability to perform SQL-like queries against relational databases, as well as specialized queries for each type of non-relational data. It allows to increase the efficiency of process0ng both relational and non-relational data, which makes it a powerful tool for analyzing and processing information from various sources. The development of virtual data warehouses may be associated with the introduction of new technologies, such as artificial intelligence, blockchain, quantum computing, etc. In addition, further improvements in metadata management and data security are expected.

The effectiveness of a virtual fencing technology to allocate pasture and herd cows to the milking shed

Virtual fencing technology provides an opportunity to rethink the management of intensive grazing systems in general, yet most studies have used products developed and applied to more extensive livestock systems. This research aimed to assess the application of a virtual fencing technology developed for the intensive pastoral dairy industry. The Halter system uses 2 primary cues, sound and vibration, and one aversive secondary cue, a low energy electrical pulse, to confine cows to a pasture allocation and remotely herd cows. Two groups of 40 mid-lactation multiparous dairy cows were studied (Bos taurus, predominantly Friesian and Friesian × Jersey, parity 1-8). Cows were milked twice per day and provided 9 kg pasture DM/day in a 24-h allocation, supplemented with 7 kg silage and 6 kg grain DM/day. Training to the Halter system occurred over 10 d after which cows were managed with the technology for a further 28 d. The type and time of cues delivered was recorded by each collar and communicated via a base-station to cloud data storage. Cows took less than a day to start responding to the sound cues delivered while held on a pasture allocation and were moving to the milking parlor without human intervention by d 4 of training. On training d 1, at least 60% of sound cues resulted in an electrical pulse. Across training d 2-10, 6.4% of sound cues resulted in a pulse. After the 10-d training period, 2.6% of sound cues resulted in a pulse. During the management period, 90% of cows spent ≤1.7 min/d beyond the virtual fence, received ≤ 0.71 pulse/d in the paddock and received ≤ 1 pulse/d during virtual herding to the parlor. By the final week of the management period, 50% of cows received zero pulses/week in the paddock and 35% received zero pulses/week during virtual herding. The number of pulses delivered per day and the pulse:sound cue ratio was lower in this study than that previously reported using other virtual fencing technologies. We conclude that the Halter technology is successful at containing lactating dairy cows in an intensive grazing system as well as at remotely herding animals to the milking parlor.

Blockchain-assisted post-quantum privacy-preserving public auditing scheme to secure multimedia data in cloud storage

Blockchain-assisted post-quantum privacy-preserving public auditing scheme to secure multimedia data in cloud storage

Duplicate Detection on Cloud Data with Re-Encryption Based Data Sharing

Cloud data storage has gained immense popularity in recent years due to its scalability and accessibility. However, the efficient management of data in the cloud, especially with the ever-increasing volume of data, remains a significant challenge. Data deduplication is a crucial technique to reduce storage costs and enhance data management efficiency. It also concerns the secure cloud data storage and sharing. Here implement a novel approach to de duplication-based cloud data storage using chunk-based partitioning. In this approach, data is divided into fixed-size chunks, and a deduplication mechanism is applied to identify and eliminate redundant chunks. The process of duplicate detection leading to improved storage efficiency and reduced data redundancy. It not only conserves storage space but also enhances data retrieval performance by reducing the volume of data to be transferred over the network. Proposed system also enhance the security of cloud data storage by employing Base64 encoding for data representation and implementing re-encryption techniques based on the Advanced Encryption Standard (AES) for secure data sharing. The Base64 encoding methodology is employed to transform binary data into a text format, rendering it less susceptible to unintended manipulations during data transmission and storage. This encoding mechanism ensures data integrity and facilitates its secure storage in cloud environments. By utilizing AES encryption, data shared among users is re-encrypted with unique keys, ensuring that only authorized recipients can access and decrypt the shared information. The proposed approach significantly enhances data confidentiality and mitigates risks associated with unauthorized access, there by fortifying the security of cloud-based data sharing.

Secure Date Storage Using ECC Encryption with Verifiable Data Sharing in Cloud

Cloud data storage has become increasingly popular, but the security and privacy of data stored in the cloud remain major concerns. Cloud computing is the most feasible approach for implementing Digital Twin services since it has prodigious advantages. It provides on demand services, computing resources, ubiquitous network access, etc., making it suitable for the next-generation information technology architecture. In cloud-assisted data storage environments, the data owners generate data from physical assets and disseminate it to the cloud server.

Peer-to-Peer Network Node Distribution Analysis Using Block chain

This project uses block chain technology to propose a decentralized access control method for anonymous authentication and secure cloud data storage. The suggested plan improves privacy by guaranteeing that users can authenticate themselves to the cloud without disclosing who they are. Block chain integration improves system security by removing single points of failure and enabling robust, decentralized access management. The plan handles user revocation, enables fine-grained access control, and successfully thwarts replay assaults. Users have similar communication, processing, and storage overheads to centralized methods when creating, editing, and reading material that is stored on the cloud. Our method is decentralized, which sets it apart from conventional models and makes it a useful and effective way to store data securely on the cloud for applications that need a high degree of trust.

ХМАРНІ ТЕХНОЛОГІЇ В СИСТЕМАХ ПІДТРИМКИ ПРИЙНЯТТЯ РІШЕНЬ

The paper considers a cloud management strategy. The main theoretical and practical aspects of the use of cloud computing services and cloud data storage, used as a key component of a decision support system used in the interests of system administrators, researchers, business analysts and top managers

The Role of Cloud Storage in Rebuilding Governmental Data After Conflict: A Case Study of Sudan 2023

The aim of this research is to assess the Role of Cloud Storage in Rebuilding Governmental Data After Conflict, with a deeper insight into Sudanese case. To investigate the role of cloud storage in rebuilding governmental data after conflict in Sudan, this study employs a quantitative research methodology. The primary data collection instrument is a structured questionnaire designed to gather insights and perspectives from 80 participants of key stakeholders involved in the cloud storage adoption and data reconstruction efforts in Sudan, including (IT professionals and data management experts, Senior-level government officials and policymakers, Representatives from cloud service providers, End-users and data consumers from various government agencies). The collected data underwent accurate statistical analysis, including descriptive and inferential techniques, to identify patterns, trends, and relationships among the variables under investigation. Quantitative data was analyzed using "SPSS" statistical software. The findings of the research revealed that, a total of 18 participants representing (22.5%) agree that there is a high level of awareness and understanding of cloud storage technologies among government agencies in Sudan, while 28 participants representing (35%) disagree. Which indicates the need of spreading the awareness and understanding of cloud storage technologies among government agencies in Sudan. Furthermore, Pearson Chi-Square test was used to measure the role of cloud storage in rebuilding governmental data after conflict in Sudan, a significance value of (0.021) which is less than (p-value=.05) suggests that there is a significant role of cloud storage in rebuilding governmental data after conflict in Sudan.

Integrated Service Architecture to Promote the Circular Economy in Agriculture 4.0

Innovation has been the transforming tool of precision agriculture as a response to population growth and the demand for more food with quality, less waste, food security, and sustainable management of environmental resources. The challenges are to increase the productivity of cultivated areas, both for current and future areas, to manage the use of potable water, scarce in many regions, to keep the soil fertile, and to reduce waste through reuse, optimization, resource sharing, and operational and strategic management based on accurate information of planting, harvesting, and management of environmental conditions, which are also objectives of the Circular Economy. Therefore, using Industry 4.0 technologies in agriculture becomes fundamental to facing such challenges. This paper presents a systematic literature review on Industry 4.0 technologies adopted in agriculture for sustainable development, considering environmental, economic, and social benefits. The research pointed to the use of IoT in irrigation control systems by sending automatic commands, monitoring soil and weather conditions, in the use of machinery with some automation features and in cloud data storage systems, and with the use of Big Data analytical tools, with access by mobile devices, these uses contribute to operational and strategic decision making in the management of planting and harvesting. However, the literature review did not find a technological architecture for Integrated Services in Agriculture 4.0. Thus, this paper proposes a Service Architecture that enables the promotion of a Circular Economy in Agriculture 4.0. The contribution of this article to the theory is in the expansion of knowledge of the use of technologies in Agriculture 4.0. In terms of practice, this article provides an Integrated Service Architecture so that new products can be developed for Agriculture 4.0 and thus contribute to society in reducing food insecurity, generating environmental, economic, and social benefits, and promoting the Circular Economy in Agriculture 4.0.

Multi User Authentication for Reliable Data Storage in Cloud Computing

Today's digital environment, Multi-user authentication plays a crucial role in ensuring data integrity and confidentiality, emphasizing its importance of reliable and secure data storage in cloud computing environments. The exploration extends to the strategies for implementing secure multi-user authentication, encompassing aspects such as password policies, biometric verification, encryption, role-based access control (RBAC), and multi-factor authentication (MFA). The issue of reliable data storage is covered in further detail, on the importance of data availability and integrity. Real-world applications of multi-user authentication and reliable data storage are examine. The paper elucidates how these applications enhance overall security, mitigating risks associated with unauthorized access and cyber threats.The paper concludes by integration of multi-user authentication and reliable data storage is explored through considerations the critical role of multi-user authentication in ensuring reliable data storage in cloud computing such as secure API access, token-based authentication, and adherence to security best practices. Challenges in user authentication are addressed, with solutions proposed for seamless access across cloud platforms, including the adoption of Single Sign-On (SSO), multi-factor authentication, regular security audits, collaboration with cloud security experts, and user education and training. The synthesis of challenges, benefits, drawbacks, and implementation strategies provides organizations with a comprehensive guide for enhancing their data security measures.

"Cloud Storage of Data and the Crime of Storage of “Electromagnetic Records” under Criminal Law in Japan"

"Cloud Storage of Data and the Crime of Storage of “Electromagnetic Records” under Criminal Law in Japan"

Building Feedback-Regulation System Through Atomic Design for Highly Active SO2 Sensing.

Reasonably constructing an atomic interface is pronouncedly essential for surface-related gas-sensing reaction. Herein, we present an ingenious feedback-regulation system by changing the interactional mode between single Pt atoms and adjacent S species for high-efficiency SO2 sensing. We found that the single Pt sites on the MoS2 surface can induce easier volatilization of adjacent S species to activate the whole inert S plane. Reversely, the activated S species can provide a feedback role in tailoring the antibonding-orbital electronic occupancy state of Pt atoms, thus creating a combined system involving S vacancy-assisted single Pt sites (Pt-Vs) to synergistically improve the adsorption ability of SO2 gas molecules. Furthermore, in situ Raman, ex situ X-ray photoelectron spectroscopy testing and density functional theory analysis demonstrate the intact feedback-regulation system can expand the electron transfer path from single Pt sites to whole Pt-MoS2 supports in SO2 gas atmosphere. Equipped with wireless-sensing modules, the final Pt1-MoS2-def sensors array can further realize real-time monitoring of SO2 levels and cloud-data storage for plant growth. Such a fundamental understanding of the intrinsic link between atomic interface and sensing mechanism is thus expected to broaden the rational design of highly effective gas sensors.

Design of cloud data storage security and financial risk control management early warning system based on sensor networks

The wide application of sensor networks has brought great challenges to cloud data storage, such as transmission security, data privacy protection and financial risk control. In order to deal with these challenges, the system establishes a comprehensive management early warning system to ensure the data security and financial risk control of the sensor network. The system integrates sensor network technology and cloud data storage technology, and stores data in the cloud through the collection and transmission of environmental data by sensor nodes. In order to ensure the security of the stored process, the system adopts a series of security mechanisms, such as data encryption, access control and identity authentication, and also introduces the financial risk control module, which helps users to warn and manage financial risks through real-time monitoring and analysis of data in the sensor network. The system provides a user-friendly management interface, allowing users to easily configure and monitor the operating state of the sensor network, and supports flexible expansion and customization to adapt to the needs of different scenarios. Through the application of this system, users can effectively manage and control the security and financial risks of sensor networks in cloud data storage, and improve the efficiency and reliability of data storage management.

Access control and data sharing mechanism in decentralized cloud using blockchain technology

<p class="abstract">Access control is the most vital aspect of cloud data storage security. Traditional techniques for data distribution as well as access control face noteworthy challenges in the arena of research as a result of extensive abuse and privacy data breaches. The blockchain concept provides security by verifying users by multiple encryption technologies. Collaboration in the cloud improves management but compromises privacy. Consequently, we created an efficient access management and data exchange system for a blockchain-based decentralized cloud. On the basis of an ID and password, the data user (DU) submits a registering request to the data owner (DO). The DO data is incorporated into a transactional blockchain by an encoded master key. The data owner (DO) provides data encryption, and encrypted files are still published to the Interplanetary File System (IPFS). The DO generates ciphertext metadata, which is then published to the transactional blockchain utilizing a secure file location and a secure key. The projected access control and data sharing solution performed better in a decentralized blockchain based cloud, as measured by metrics such as a reduced illegitimate user rate of 5%, and a size blockchain of is 100 and 200, respectively.<strong><em></em></strong></p>

BGNBA-OCO based privacy preserving attribute based access control with data duplication for secure storage in cloud

Cloud computing technology offers flexible and expedient services that carry a variety of profits for both societies as well as individuals. De-duplication techniques were developed to minimize redundant data in the cloud storage. But, one of the main challenges of cloud storage is data deduplication with secure data storage.To overcome the issue, we propose Boneh Goh Nissim Bilinear Attribute-based Optimal Cache Oblivious (BGNBA-OCO) access control and secure de-duplication for data storage in cloud computing in this paper. The proposed method achieves fne-grained access control with low computation consumption. We design Boneh Goh Nissim Privacy Preserving Revocable Attribute-based Encryption that reinforces attribute revocation and averts the discharge of sensitive information. Furthermore, we utilize Optimal Cache Oblivious algorithm to prevent disclosure of access patterns to hide the access patterns in cloud storage via rand pattern matching. We support updating both encrypted data and access control policies to minimize communication and computation overhead of data duplication and encryption processes concurrently. We perform secure data sharing to achieve higher data confidentiality and integrity. Finally, we conducted the extensive experiments in cloud and the results illustrated that our proposed BGNBA-OCO method is more efficient than related works.

Secured big data storage in cloud by intelligent authentication and privacy preservation via intelligent deep learning-aided heuristic strategy

Secured big data storage in cloud by intelligent authentication and privacy preservation via intelligent deep learning-aided heuristic strategy