Data Storage Algorithm Research Articles

Secure and efficient data storage with Rivest Shamir Adleman algorithm in cloud environment

Cloud computing rapidly is a prerequisite and releases resources with minimal management effort. The surfacing of the cloud has significantly distorted the general insight into infrastructure, software services, and development models. In contrast to single-key encryption models based on public or private keys (PKs), hybrid encryption systems combine encryption methods using symmetric or asymmetric methods. Various hybrid algorithms fail to meet users’ expectations regarding data security and cannot prevent all security risks. The secure and efficient data storage and retrieval (SEDSR) algorithm was developed for scalable key management between the content owner, cloud user, and service providers in an un-trusted cloud environment. In the implementation, the SEDSR combines the Rivest Shamir Adleman (RSA) algorithm 4096 key length with a primary symmetric key method to provide adequate and compact security with optimal retrieval systems in the cloud. Based on the experimental evaluation, the SEDSR minimizes 1.7 seconds of encryption times (ET) and 1.5 seconds of decryption time (DT) and improves by 34% throughput (TRP) compared to existing parameters.

CFNet: An infrared and visible image compression fusion network

Image fusion aims to acquire a more complete image representation within a limited physical space to more effectively support practical vision applications. Although the currently popular infrared and visible image fusion algorithms take practical applications into consideration. However, they did not fully consider the redundancy and transmission efficiency of image data. To address this limitation, this paper proposes a compression fusion network for infrared and visible images based on joint CNN and Transformer, termed CFNet. First of all, the idea of variational autoencoder image compression is introduced into the image fusion framework, achieving data compression while maintaining image fusion quality and reducing redundancy. Moreover, a joint CNN and Transformer network structure is proposed, which comprehensively considers the local information extracted by CNN and the global long-distance dependencies emphasized by Transformer. Finally, multi-channel loss based on region of interest is used to guide network training. Not only can color visible and infrared images be fused directly but more bits can be allocated to the foreground region of interest, resulting in a superior compression ratio. Extensive qualitative and quantitative analyses affirm that the proposed compression fusion algorithm achieves state-of-the-art performance. In particular, rate–distortion performance experiments demonstrate the great advantages of the proposed algorithm for data storage and transmission. The source code is available at https://github.com/Xiaoxing0503/CFNet.

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.

Digital media and interactive E-learning application in art teaching process based on big data platform

Digital media art integrates multiple fields such as art teaching, computer graphics, and AI. With the application of new computer technologies such as artificial intelligence, serving art education through network technology has become increasingly popular. This article studies the application of digital media and interactive E-learning based on big data platforms in the process of art teaching.It can facilitate the sharing of educational resources, enable collaborative learning, and support the development of new educational models that are more efficient and effective. By analyzing the needs of students for mobile learning and personalization, this article adopts data storage algorithms and their improved algorithms as a method to improve the electronic learning system, thereby achieving the digital and networked development of art education and providing a new model for the e-learning teaching mode of art courses.

Implementing Quantum Resistant Algorithm in Blockchain-Based Applications

With quantum computing evolving very fast as we speak, the security and integrity of blockchain-based applications will become the most crucial aspect. A proposal is raised to use blockchain technology as a platform for writing and probating ‘wills’. Blockchain technology in drafting and probating wills makes them safe from manipulations, highly secure, and transparent. It also dramatically decreases the time required without catering for the challenges created by the current system. [9] This paper presents a new method for will transfer and inheritance management by implementing quantum-resistant algorithms in the security architecture of a blockchain decentralized application (DApp). The system uses IPFS Network for data storage and quantum-safe algorithms as retrieval and sending algorithms. The system includes Quantum-Resistant Dilithium Signatures and Merkle trees as the fundamental components for safeguarding the transfers of assets and claims for inheritance. Quantum-Resistant Dilithium Signatures offer an unbreakable shield against quantum attacks that are expected to happen, which in turn safeguards the privacy and authenticity of transactions. While Merkle trees are responsible for the organization of inheritance claims in an effective and tamper-proof manner, the introduced system incorporates smart contracts to address the execution of an inheritance case, adding more security and automation to the asset distribution process. The system ensures a robust security framework by integrating quantum-resistant algorithms at the very core of the blockchain DApp for instance, retrieval and sending. This research is of great significance to blockchain technology which is the emerging technology of the future because it addresses the existing threat of quantum computing by showing the feasibility of using quantum-resistant algorithms in practical applications. As established by the findings, besides Quantum-Resistant Dilithium Signatures and Merkle trees, the systems of asset transfers and inheritance management within blockchain networks are enhanced in terms of safety and reliability. Hence, paving the road to the creation of more secure and trustworthy digital asset management systems.

The impact of scale on extracting urban mobility patterns using texture analysis

The development of high-precision location tracking devices and advancements in data collection, storage, transmission technologies, and data mining algorithms have led to the availability of large datasets with high spatiotemporal resolution. These geospatial big data can be used to identify human movement patterns in urban areas. However, identifying human movement patterns may yield different results depending on the scale size used. In this paper, we employed first and second order texture analysis algorithms to identify spatial patterns of human movement for various scale sizes based on taxi trajectory data from Nanjing, China. The results demonstrated that texture analysis can quantify changes in human movement patterns for different scale sizes in an urban area. Furthermore, the results may differ based on the location of the study area. This study contributed both methodologically and empirically. Methodologically, we used texture analysis to examine the impact of different scale sizes on the extraction of aggregated human travel patterns. Empirically, we quantified the effects of different scale sizes on extracting aggregated travel patterns of an urban area. Overall, the findings of this study can have significant implications for urban planning and policy-making, as understanding human movement patterns at different scales can provide valuable insights for optimizing transportation systems and enhancing overall urban mobility.

Consensus algorithm for medical data storage and sharing based on master–slave multi-chain of alliance chain

Consensus algorithm for medical data storage and sharing based on master–slave multi-chain of alliance chain

Stochastic Gradient Descent long short-term memory based secure encryption algorithm for cloud data storage and retrieval in cloud computing environment

With the increasing rise of distributed system technologies, one of the most pressing problems facing the digital world is ensuring the security of sensitive and confidential data during transport and storage, which is also regarded as one of the most critical difficulties facing cloud computing. Numerous techniques exist for enhancing data security in the cloud computing storage environment. Encryption is the most important method of data protection. Consequently, several accessible encryption strategies are utilized to provide security, integrity, and authorized access by employing modern cryptographic algorithms. Cloud computing is an innovative paradigm widely accepted as a platform for storing and analysing user data. The cloud is accessible via the internet, exposing the data to external and internal threats. Cloud Service Providers (CSPs) must now implement a secure architecture to detect cloud intrusions and safeguard client data from hackers and attackers. This paper combines Stochastic Gradient Descent long short-term memory (SGD-LSTM) and Blow Fish encryption to detect and prevent unauthorized cloud access. User registration, intrusion detection, and intrusion prevention are the three phases of the planned system. The SGD-LSTM classifier predicts cloud data access and prevents unauthorized cloud access. In the data access phase, cloud data access is managed by authenticating the authorized user with the Blowfish encryption algorithm. Comparing the proposed classifier to existing classifiers demonstrates that it detects abnormal access accurately. The experimental outcomes enhanced data security, which can be utilized to protect cloud computing applications. The experimental results of the suggested SGD-LSTM algorithm indicated a high level of protection, as well as a considerable improvement in security and execution speed when compared to algorithms that are often used in cloud computing.

Agent Data Encryption and Storage Algorithm for Wireless Sensor Networks Based on Blockchain Technology for Future Smart City Networks

Abstract Aiming at the problems of long storage time and low encryption accuracy of the traditional agent data encryption storage algorithm in wireless sensor networks, an agent data encryption storage algorithm based on blockchain technology is proposed. Analyze the blockchain hierarchy and data, take the sensor node with the signal energy value exceeding the predetermined threshold as the source node for generating sensing data, and obtain the agent data transmission path of the wireless sensor network. Based on the obtained agent data transmission path in the data layer of data block, the agent data are encrypted by generating an encryption key and data encryption. According to the agent data encryption results, the agent data encryption storage model of the wireless sensor network is constructed. The simulation results show that the proposed algorithm has shorter storage time and higher encryption accuracy.

Industry 4.0 Oriented Distributed Infographic Design

Since industry 4.0 was put forward in 2013, industrial process around the world has been moving rapidly towards the age of intelligent manufacturing. Industry 4.0 is known as the fourth industrial revolution dominated by intelligent manufacturing, which has changed the production mode of global manufacturing and triggered far-reaching industrial changes. However, when intelligent machines communicate with each other under industrial 4.0, a large amount of data adopting distributed control will be generated. The infographic in the data is mainly a visual design of industry 4.0 data. Therefore, this paper mainly studies the distributed data optimization processing for industry 4.0. Considering that data leakage is one of the biggest challenges faced by the data storage systems, this paper proposes a data storage method that considers the efficiency and security of data access. The concept of security distance not only guarantees data security but also takes into account the emphasis of different user groups on data security. To minimize data access time, this paper proposes a data access node selection algorithm to minimize data access time while ensuring data security. The simulation proves that compared with baselines, the data access time of the proposed algorithm in random topology and Internet2 topology is less than that of the current data storage algorithm while ensuring data security. The experimental results are simulated on Internet2 topology and random topology with Matlab and Omnet + + simulation platform, showing that the proposed algorithm can select the optimal data storage node under the condition of satisfying the security distance constraint, thus reducing the data access time.

An enhanced bacterial foraging optimization algorithm for secure data storage and privacy-preserving in cloud

An enhanced bacterial foraging optimization algorithm for secure data storage and privacy-preserving in cloud

Compression and Storage Algorithm of Key Information of Communication Data Based on Backpropagation Neural Network

This paper presents a backpropagation neural network algorithm for data compression and data storage. Data compression or establishing model ten coding is the most basic idea of traditional data compression. The traditionally designed ideas are mainly based on reducing the redundancy in the information and focus on the coding design, and its compression ratio has been hovering around dozens of percent. After the traditional coding compression of information, it is difficult to further compress by similar methods. In order to solve the above problems, the information that takes up less signal space can be used to represent the information that takes up more signal space to realize data compression. This new design idea of data compression breaks through the traditional limitation of relying only on coding to reduce data redundancy and achieves a higher compression ratio. At the same time, the information after such compression can be repeatedly compressed, and it has a very good performance. This is the basic idea of the combination of neural network and data compression introduced in this paper. According to the theory of multiobjective function optimization, this paper puts forward the theoretical model of multiobjective optimization neural network and studies a multiobjective data compression method based on neural network. According to the change of data characteristics, this method automatically adjusts the structural parameters (connection weight and bias value) of neural network to obtain the largest amount of data compression at the cost of small information loss. This method has the characteristics of strong adaptability, parallel processing, knowledge distributed storage, and anti-interference. Experimental results show that, compared with other methods, the proposed method has significant advantages in performance index, compression time and compression effect, high efficiency. and high-quality robustness.

Innovation of Corporate Governance: A Discussion based on Blockchain Technology

Blockchain, as a newly-born application of computer technology, has unique advantages in data storage, point-to-point transmission, consensus mechanism and encryption algorithm, which could lead to innovation of corporate governance. The application of blockchain technology in corporate governance has attracted more and more attention as it provides new approaches to improve corporate innovation ability as well as operation efficiency. This paper will discuss three types of applications of blockchain technology in corporate governance, including operating based on DAO, creating employee performance appraisal and incentive mechanism and cooperating among Multi-departmental employees. There are three aspects that will be included in the discussion of each application, namely mechanism, preconditions and benefits, so as to show the potentials of blockchain technology comprehensively. Furthermore, this paper will provide detailed design of corporate governance model, including the structure of Blockchain-based platforms, design of operating system and design of appraisal and incentive system, which offers a guideline to corporations that intends to adopt blockchain technology in their corporate governance.

Protection Aware User Identity and Data Storage (PAUIDS) Scheme for Management of User Identification in Cloud

Cloud computing the technology which have the capability of modifying the method computing strongly, and storage resources will be accessed shortly. User Identification is an entity to detect the user who using the system or website. In information technology the protection of information consistently become a major issue to handle. The data might place in various locations in the world since it become particularly serious. The two main factors regarding cloud technology are information protection and security. The cloud operators can easily reach the sensitive information that affects the data security and protection measures. Therefore, this research protocol mainly focuses on secure data storage that always been a significant feature of quality of service. To guarantee the ‘rightness of users’ information in cloud storage system a Protection Aware User Identity and Data Storage (PAUIDS) algorithm is proposed that separates the document and independently stores the user information in the cloud storage servers. The proposed algorithm reduces the encryption and decryption time in a cloud storage system and providing secure and efficient data storage in cloud environments.

Blockchain Technology as an Alternative Method of Payment Transaction Proof

Today, the development of information technology allows all needs in the payment system to conduct safely and reliably with the support of blockchain technology. Blockchain technology is currently a concept getting more attention in financial technology (Fintech). This technology combines several computer technologies, including distributed data storage, point-to-point transmission, consensus mechanisms, and encryption algorithms often referred to as cryptography. Currently, various payment methods are available, Direct payment methods via the website, credit cards, automatic debit (Autopay), Mobile / Internet Banking, Non-bank, E-commerce, and E-wallet. All of the above payment systems still require a third party as a guarantor for the transactions made. Another problem that arises is a notification of bill dues to consumers, using conventional media in letters, emails, and notices of short message service (SMS), which allows consumers to miss the given deadline. It could cause the service to terminate. Blockchain technology is currently still considered an innovation that disrupts the world of banking and the internet. However, because this technology is a breakthrough major in data storage and information transmission, it will fundamentally change the global financial and economic operating model towards new technologies and industrial transformation in the financial industry. Current consumer bill payment methods use conventional banking systems, and notification systems for payment deadlines are less efficient; we propose a payment system with blockchain technology and the internet of things (IoT) to solve the current problem.

A Robust Lightweight Data Security Model for Cloud Data Access and Storage

In this paper, an efficient lightweight cloud-based data security model (LCDS) is proposed for building a secured cloud database with the assistance of intelligent rules, data storage, information collection, and security techniques. The major intention of this study is to introduce a new encryption algorithm to secure intellectual data, proposing a new data aggregation algorithm for effective data storage and improved security, developing an intelligent data merging algorithm for accessing encrypted and original datasets. The major benefit of the proposed model is that it is fast in the encryption process at the time of data storage and reduced decryption time during data retrieval. In this work, the authors proposed an enhanced version of the hybrid crypto algorithm (HCA) for cloud data access and storage. The proposed system provides secured storage for storing data within the cloud.

OCEDS

Many organizations require handling a massive quantity of data. The rapid growth of data in size leads to the demand for a new large space for storage. It is impossible to store bulk data individually. The data growth issues compel organizations to search novel cost-efficient ways of storage. In cloud computing, reducing an execution cost and reducing a storage price are two of several problems. This work proposed an optimal cost-effective data storage (OCEDS) algorithm in cloud data centres to deal with this problem. Storing the entire database in the cloud on the cloud client is not the best approach. It raises processing costs on both the customer and the cloud service provider. Execution and storage cost optimization is achieved through the proposed OCEDS algorithm. Cloud CSPs present their clients profit-maximizing services while clients want to reduce their expenses. The previous works concentrated on only one side of cost optimization (CSP point of view or consumer point of view), but this OCEDS reduces execution and storage costs on both sides.

Using Blockchain Technology to Enhance the Traceability of Original Achievements

The protection of original achievements including patents and copyrights is a significant and critical issue in today's knowledge-driven economy. In this article, we propose and develop a blockchain service architecture to enhance information traceability and protection effectiveness. Our proposed service architecture is enabled by the core functionalities of blockchain technology including distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Through this blockchain-based traceability system, we can record, secure, validate, and track original achievements’ registrations and other related transactions. The results of our simulation experiments further validate the effectiveness and robustness of the proposed traceability system design. Our experimental analysis shows that the proposed blockchain-based design can effectively enhance original achievements traceability with an embedded automatic incentive rewarding mechanism for both the creation and protection of original achievements. Moreover, our performance analysis and comparative analysis show that the proposed method has more advantages over several other methods. While our study provides an effective solution to address the existing challenges in intellectual property rights and achievements patents protection, the breadth of the blockchain concept and its applications require nuanced investigations in many different contexts. Thus, the proposed blockchain-based traceability system highlights the potential for broader applications of this disruptive technology in many other domains.

A trust-based fuzzy neural network for smart data fusion in internet of things

Internet of Things (IoT) devices generates a vast amount of data from extensive applications. Maintaining the sensed data with low energy consumption, delay time, and adaptive coverage fraction rate proportionally influences the storage capacity. To maintain a trade-off between above-listed factors, we proposed an Elfes Sugeno Fuzzy and Trust-based Neural Networks (ESF-TNN) approach enables 3-algorithms. First, Elfes Probability Sensing (EPS) Model addresses the coverage fraction of each IoT sensor. Second, Sugeno Fuzzy Processing model regulates the energy consumption by proportionately distributing data to nodes without the defuzzification process. Third, Trust-based Neural Data Storage algorithm enriches an adequate data storage capacity by considering the average classification ratio while processing regenerated data packets to pertain each interaction information via Trust Mechanism. Simulation results show that our proposed method effectively covers the monitored area with 15 Joules of energy consumption and 1-ms delay time along with sufficient storage capacity.

A Medical Data Privacy Protection Scheme Based on Blockchain and Cloud Computing

With the features of decentralization and trustlessness and through distributed data storage, point-to-point transmission, and encryption algorithms, blockchain has shed new light on the security and protection of medical data, and it can resolve the contradiction between data sharing and privacy protection with proper security strategies. In this paper, we integrate the strengths of both blockchain and cloud computing and build the privacy protection scheme for medical data based on blockchain and cloud computing. This scheme introduces cloud computing and provides services to blockchain nodes with cloud server computing; meanwhile, it collects, analyzes, processes, and maintains medical data in the identity authentication interface and solves the insufficient computing abilities of some nodes in blockchain so as to verify the authenticity and reliability of data. The simulation experiment proves that the proposed scheme is effective. It can achieve the secure protection and integrity verification of medical data and address the problems of high computing complexity, data sharing, and privacy protection.