Secure Cloud Data Storage Research Articles

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.

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.

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.

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>

Analysis of Secured Cloud Data Storage Model for Information

Analysis of Secured Cloud Data Storage Model for Information

Online/offline remote data auditing with strong key-exposure resilience for cloud storage

Remote Data Auditing (RDA) with key-exposure resilience enables secure cloud data storage both earlier and later than the key exposure happens. However, most of existing solutions suffer from the security attack during the key-exposed time period, meaning the cloud server can still discard or tamper with the data owner’s files in the key-exposure period. While others require a secure channel for key update, which is unrealistic and expensive under key-exposure scenarios. In this paper, we construct an online/offline RDA framework with strong key-exposure resilience, called S-OORDA, which can resist strong key-exposure attacks and achieve the integrity verification for cloud data efficiently. Then based on the framework, we present a concrete S-OORDA scheme supporting the data owner’s secret key evolution without the secure channel. And the authenticators can be updated remotely at each time period, so as to prevent the attackers to forge the authenticators using the exposed auditing secret keys. Meanwhile, the data auditing process of the proposed scheme is divided to online and offline phases, greatly relieving the online computational burden of both the data owner and the third-party auditor. Security and performance analysis confirm that the proposed scheme meets the desired security and has the optimized efficiency.

Trust aware cryptographic role based access control scheme for secure cloud data storage

Cloud data storage lets customers store vast amounts of data cheaply on demand. Cryptographic role-based access control (RBAC) systems preserve cloud data privacy by restricting access to users. This study develops a trust model to reason about and improve data security in cryptographic RBAC cloud storage systems. The trust degrees of the user determine the access rights to the data and are performed by User Activity Monitoring Agent (UAMA). Two different misconducts of users such as access policy violation and data leakage affect the trust degree of the user, which in turn upgrades the access policy. In addition, the user has to decrypt the data for gaining information from it, which is a second line of security. The performance of trust based RBAC scheme is evaluated with respect to different parameters such as illegitimate user detection, memory consumption, data storage with retrieval time and the proposed work performs better.

Secure cloud data storage solution with better data accessibility and time efficiency

The environment of cloud computing provides several advantages and a variety of data storage models, which entirely frees users from the vexing processes of storage equipment upgradation and data administration. Nevertheless, the customers’ primary worry is the safety of their data, and the literature offers a number of different security-based solutions for addressing this issue. This paper proposes a technique for time-efficient cloud data storage that makes use of keccak and Advanced Encryption Standard (AES) which enhances the data availability with a reasonable storage space. Third party agents are not employed, due to the fact that a third party cannot be relied upon to maintain a high level of data security. Thus, the proposed algorithm is applied by cloud users before the process of outsourcing is carried out. This method is resistant to data tamper and analytical attacks. In addition, the execution of the work that has been proposed requires a limited amount of time, which, in turn, minimizes the amount of energy that is required. In contrast to the already used algorithms, the presented work demonstrates superior performance in terms of its overall effectiveness.

SOSO: Symbiotic Organisms Search Optimization based Faster RCNN for Secure DataStorage in Cloud

Because of the Internet of Things (IoT) and wearable devices, information obtained is subject to cyber attacks, making intrusion detection an essential component. The increased number of attacks on IoT devices exposes them to ongoing exploitation and data theft. Mirai, denial of Service (DoS), scan, etc are the major types of attacks conducted on IoT. Traditional attack detection algorithms have more disadvantages like lack of adaptability in all scenarios, low local minima computational complexity, etc. Thus developing a method that is suitable for all environments and has good convergence speed is taken as the motivation of this study. This paper presents a novel Symbiotic Organisms Search Algorithm (SOSA) optimized Faster region-based convolutional neural network (FRCNN) for attack detection and data type classification. The data to be stored in the cloud is analyzed whether they have restricted access, confidential, or unclassified. Depending upon the variety of data, the Optimal homomorphic encryption (OHE) approach is provided for security. The key selection process is done by an Elastic Collision Seeker Optimization Algorithm (ECSOA) which offers secure access to the data owner and prevents the data from unauthorized access. The model is optimized using the algorithm which improves the feature extraction performance. The effectiveness of the proposed model in attack detection is evaluated using two datasets namely the CSE-CIC-ID2018 dataset and the IoTID20 dataset. When compared to the existing techniques, the proposed model offers optimal performance in terms of multiclass attack detection.

An efficient and secure data sharing scheme for cloud data using hash based quadraplet wavelet permuted cryptography approach

SummaryEnsuring the reliable and secure data transmission in cloud systems is very essential and demanding task in the recent decades. For that purpose, various security frameworks have been deployed in the existing works, which are mainly focusing the improving the privacy and confidentiality of cloud data against the unauthenticated users. Yet, it facing the major problems of inefficient accessing, increased time consumption, computational complexity, storage complexity, and memory utilization rate. Hence, this research work intends to develop an advanced and efficient cryptography model, named as, hash based quadraplet wavelet permuted cryptography (HQWPC) for the secured cloud data storage and retrieval operations. Here, the bilinear mapping and group hash function generation processes are performed to generate the keys used for cryptographic operations. Also, the zig‐zag scanning, wavelet coefficients extraction, and permutation processes are accomplished for data encryption. Consequently, the inverse of these operations is performed while decrypting the data. In addition to that, an integrated signature control policy authentication mechanism is employed for validating the authenticity of the cloud data users. This kind of signature verification process could efficiently increase the security level of cloud data. For validating the performance of the proposed security framework, various evaluation metrics have been utilized during analysis. Then, the obtained results are compared with the recent state‐of‐the‐art models for proving the efficiency of the proposed technique over the other techniques.

Secured Cloud Data Storage Encryption Using Post-Quantum Cryptography

Secured Cloud Data Storage Encryption Using Post-Quantum Cryptography

A Secured Storage and Communication System for Cloud Using ECC, Polynomial Congruence and DSA

Security is necessary for performing the effective data communications in internet and cloud environment. The data security in cloud is becoming very challenging task due to the presence of huge volume of cloud users. Even though, the various secured cloud data storage mechanisms are available and tried to fulfill the current requirement in terms of security level and efficiency. However, the available works are not obtained the enough security level and the efficiency while storing and sharing the data in cloud. For this purpose, this work proposes a new secured storage method for providing data security to store the data securely in cloud. The proposed system consists of three different algorithms for performing prime number generation, digital signature creation for generating keys, encryption, decryption and authorization. Here, a new technique to find a co-prime number which is used to generate keys in key generation process and also useful for performing encryption and decryption process. Moreover, a new key generation technique is also introduced for elliptic curve cryptography and digital signature algorithm using polynomial congruence for performing key generation process securely. In addition, a new elliptic curve and polynomial congruence based encryption/decryption algorithms for performing data encryption and decryption in the process of data storage and communication. Finally, the user authenticity is verified by the proposed digital signature algorithm in this work. The experiments have been conducted for evaluating the proposed secured storage and communication system and proved as better than others in terms of efficiency and security level.

A Blockchain-Based Verifiable User Data Access Control Policy for Secured Cloud Data Storage.

Adding the adequate level of security of information systems dealing with sensitive data, privacy, or defense systems involves some form of access control. The audits performed are dealing with the determination of the allowed activities of the legal users, when attempting to access resources of the system. Usually, full access is provided after the user has been successfully authenticated through an authentication mechanism (e.g., password), while the corresponding authorization control is based on the confidentiality level of the respective resources and the authorization level assigned to each user. A very important diversification occurring in modern digital technologies is related to the identification based on blockchain technology, which is presented as a public, distributed data series, unable to modify its history and grouped in time-numbered blocks. In this work, a blockchain-based verifiable user data access control policy for secured cloud data storage is suggested for a version associated with big data in health care. It is an innovative system of applying classified access policies to secure resources in the cloud, which operates based on blockchain technology. System evaluation is carried out by studying a case in its resilience to Eclipse attack under different malicious user capabilities for routing table poisoning.

ROBUST KEY REVELATION OF PUBLIC AUDITING PROTOTYPE FOR SECURE CLOUD STORAGE

In cloud storage the data clients can remotely store their data and use on-demand high- quality applications. Data outsourcing users are reassured from the trouble of data storage and maintenance when users put their data in huge size on the cloud, the data integrity protection is a challenging one which enabling public audit for cloud data storage security. Users can ask an external inspection of third party to check the integrity of the out sourced data. However, in such a scheme, the malicious cloud might still forge valid authenticators later than the key-revelation time period if it obtains the current secret key of Data Client. In this paper, propose a prototype named Robust Key Revelation of public auditing for secure cloud storage, in which the security of cloud storage auditing not only earlier than but also later than the key revelation can be preserved. Formalized the definition and the security model of this new kind of cloud storage auditing and design a concrete scheme. In this proposed prototype, the key revelation in one-time period doesn’t affect the security of cloud storage auditing in other time periods. The accurate security proof and the experimental results demonstrate that this proposed prototype achieves desirable security and efficiency with the time intervals. Keywords: Secure Cloud Storage, Robust Key Revelation, Security, Data Client, and Public Auditing.

Data Integrity Attacks in Cloud Computing: A Review of Identifying and Protecting Techniques

Cloud computing is growing tremendously in recent years. Many organizations are switching their traditional computing model to a cloud based because of its low cost and pay-as-you-go manner. Although Cloud Service Provider (CSP) ensures that the data stored in their remote cloud server will be intact and secure. But there are many data integrity issues exist that needed to be addressed. In Cloud environment, lack of data integrity is a major concern. In this paper, we have surveyed several past studies which identifies the issues related to the cloud data storage security such as data theft, unavailability, and data breach of cloud server data. We have also provided a detailed analysis of types of data integrity attacks and their mitigation techniques.

Efficient way to ensure the data security in cloud computing

Abstract This manuscript proposes a cloud data storage security, which has always been an important aspect of Quality of Service (QOS). Here, an effectual and flexible distributed scheme (DS) with Explicit Dynamic Data Support (EDDS) is proposed to ensure the accuracy of user data in the cloud. By using hemimorphic token with distributed verification of erasure-coded data, the proposed scheme achieves the integration of storage correctness insurance and data error localization. The proposed scheme supports secure and efficient dynamic operations on data blocks, such as data update, delete and append. The performance analysis shows that the proposed scheme is highly efficient.

M♡THer, an mHealth System to Support Women with Gestational Diabetes Mellitus: Feasibility and Acceptability Study.

Background: Gestational diabetes mellitus (GDM) is defined as glucose intolerance first identified during pregnancy. Delays in diagnosis and challenges in management can lead to serious adverse outcomes for the mother and child. As rates of GDM diagnosis increase worldwide, health systems and maternity services have become increasingly strained, especially with new restrictions around in-person care due to the current COVID-19 pandemic. Mobile health (mHealth) has increasingly shown promise for management of chronic disease, driven by smartphone adoption and increased internet connectivity. The aim of this work was to evaluate the adoption and multidisciplinary care coordination of an mHealth platform called M♡THer in a cohort of women with first-time diagnosis of GDM.Methods: The mHealth platform for GDM management was developed incorporating a smartphone application, clinician portal, and secure cloud data storage. Forty participants with a first-time diagnosis of GDM were recruited to use the app during their pregnancy. User attitudes from clinicians and women were captured through post-hoc surveys, and app-usage metrics.Results: Clinicians and women indicated satisfaction and ease of use of the mHealth platform, with some technological challenges around wireless connectivity. Blood glucose reviews and antenatal contact were higher with use of the M♡THer app compared with a matched historical sample.Conclusion: The M♡THer mHealth platform is a new comprehensive tool for health care of women with GDM, and may provide an effective new avenue to enhance multidisciplinary care in the face of COVID-19 disruptions and challenges to traditional care pathways.

Identity authentication-based load balancing with Merkle hash tree for secured cloud data storage

Cloud computing allows users to store and process the data in the cloud in a simple manner. However, cloud security and load balancing remain as demanding issues in cloud server. An identity authentication load balancing based Merkle hashing (IALB-MH) technique is introduced for the user to access the cloud services with unique identity (ID). Initially each cloud user sends their ID to the CS for registration. The cloud service provider checks whether the user has authenticated or not by matching the cloud user ID with the ID in CS. Therefore, a load balancing is performed by avoiding the unauthorised access to data. A Merkle hash tree is constructed to store the user data with hash values in a secured manner with minimal storage space. Experimental evaluation is carried out on load balancing efficiency, attack detection rate, space and time complexity with respect to a number of cloud users and data.

Enabling Ternary Hash Tree Based Integrity Verification for Secure Cloud Data Storage

Cloud Computing enables the remote users to access data, services, and applications in on-demand from the shared pool of configurable computing resources, without the consideration of storage, hardware, and software management. On the other hand, it is not easy for cloud users to identify whether Cloud Service Provider's (CSP) tag along with the data security legal expectations. So, cloud users could not rely on CSP's in terms of trust. So, it is significant to build a secure and efficient data auditing framework for increasing and maintaining cloud users trust with CSP. Researchers suggested introducing Third Party Auditor (TPA) on behalf of cloud user for verifying the outsourced data integrity, which may reduce the computation overhead of cloud users. In this work, we proposed a novel integrity verification framework for securing cloud storage based on Ternary Hash Tree (THT) and Replica based Ternary Hash Tree (R-THT), which will be used by TPA to perform data auditing. Differing from existing work, the proposed framework performs Block-level, File-level and Replica-level auditing with tree block ordering, storage block ordering for verifying the data integrity and ensuring data availability in the cloud. We further extend our framework to support error localization with data correctness, dynamic updates with block update, insert, and delete operations in the cloud. The structure of THT and R-THT will reduce the computation cost and provide efficiency in data updates compared to the existing schemes. The security analysis of the proposed public auditing framework indicates the achievement of desired properties and performance has been evaluated with the detailed experiment set. The results show that the proposed secure cloud auditing framework is highly secure and efficient in storage, communication, and computation costs.