Multi-cloud Storage System Research Articles

Enhancing Multi-Cloud Storage: A Hybrid Framework Using Interleaving and LT Codes

This article presents a novel framework for enhancing the integrity and availability of data stored on multi-cloud storage systems. The proposed technique leverages a combination of interleaving and Luby transform (LT) codes, specifically employing either ideal or robust soliton distribution during the LT encoding stage. The proposed technique is rigorously designed, incorporating data preparation facilitated by a cloud broker and culminating in the measurement of key performance indicators (KPIs). A central component of the framework is data processing, which involves interleaving followed by the LT encoding with soliton distribution selection. The performance of the proposed technique is evaluated through data integrity, data availability, and others. The results demonstrate that using the robust soliton distribution offers a pragmatic balance between computational efficiency and robust data integrity, particularly crucial in dynamic multi-cloud environments. Additionally, the proposed technique achieves a high level of data integrity of more than 0.97 and strong resilience with average data availability of 98%. However, further optimization is necessary to address storage overhead, retrieval time, and computational overhead. Despite these considerations, the framework remains significant, especially within the context of confidentiality, integrity, and availability for multi-cloud storage protection. The proposed technique underscores the potential of integrating interleaving and LT codes to revolutionize data storage and access within cloud environments, paving the way for future innovations in the field.

Cloud in Blockchain Technologies

Cloud computing and blockchain technology have become essential ideas in the field of IT, providing new ways to handle data. Cloud computing offers internet-based access to computing resources like servers and storage, while blockchain guarantees the accountability and immutability of data transactions with its distributed ledger system. Combining these technologies can enhance organizations' capabilities in data security and management. Businesses can utilize scalable infrastructure on cloud platforms by implementing blockchain technology, eliminating the need for large investments in physical resources. This integration improves the ability to access blockchain networks, making interactions easier across different locations and devices. Additionally, it enhances data security and privacy measures by enabling encrypted connections and strong authentication methods in cloud-based blockchain systems. Yet, obstacles remain in guaranteeing the authenticity and protection of information kept in multi-cloud settings, requiring effective authentication measures. To tackle these difficulties, this article presents a method for verifying data integrity in multi-cloud storage using blockchain technology, utilizing the decentralized aspect of blockchain to improve transparency and security. The plan automates verification procedures through smart contracts and cryptographic hashing, allowing for integrity checks at both a general and specific level across multiple Cloud Service Providers (CSPs). The proposed scheme has its effectiveness and reliability validated through theoretical analysis and experimental results, highlighting its potential to improve the security and efficiency of multi-cloud storage systems. INDEX TERMS: Cloud Computing, Blockchain Technology, Data Integrity Verification, Multi-Cloud Storage, Smart Contracts, Cryptographic Hashing, Security, Transparency.

A Blockchain-Based Multi-Cloud Storage Data Auditing Scheme to Locate Faults

The advent of network storage services has revolutionized user experiences worldwide, offering unparalleled convenience, cost-effectiveness, and robust availability. However, relying solely on a single service provider entails inherent risks. To address this, sophisticated multi-cloud storage systems have emerged, aiming to mitigate data corruption risks. Nevertheless, ensuring data integrity in such systems necessitates robust auditing schemes. Traditional approaches often depend on centralized entities like third-party auditors (TPAs) or cloud service organizers, leaving users vulnerable to malicious actors during disputes. In response, we propose a blockchain-based multi-cloud storage auditing framework. By leveraging blockchain technology, we establish an immutable ledger to record interactions among users, service providers, and organizers, serving as indisputable evidence. Smart contracts are employed to detect and resolve service disputes, compelling untrusted organizers to accurately identify malicious providers. Additionally, we utilize blockchain networks and homomorphic verifiable tags to facilitate low-cost batch verification without the need for TPAs. Theoretical analyses and empirical evaluations demonstrate the scheme's efficacy and cost-effectiveness in multi-cloud environments, promising enhanced data integrity and dispute resolution mechanisms. Keywords—Multi-cloud storage, blockchain, data auditing, dispute arbitration

An efficient and secure identity-based integrity auditing scheme for sensitive data with anti-replacement attack on multi-cloud storage

The rapid growth of cloud storage brings forth significant difficulties in ensuring the integrity of data owners' sensitive data. Multi-cloud storage systems, which motive to enhance trustworthiness, are vulnerable to rigorous replacement attacks. These insidious attacks involve malicious actors substituting legitimate data with counterfeit versions, leading to compromised integrity and fraudulent audit outcomes. We propose a novel identity-based data integrity auditing protocol tailored for multi-cloud storage environments to tackle this challenge. Our protocol leverages a Third-Party Auditor (TPA) to delegate data authenticity and auditing responsibilities, employing identity-based blind signatures with a robust data recovery scheme. By eliminating the need for cumbersome public key certificate management, our solution effectively protects data owners' sensitive data while ensuring confidentiality across multiple cloud providers, thereby mitigating the risk of replacement attacks. A thorough security examination shows the proposed system resists forging, replacement attacks, and data confidentiality violations. A rigorous performance experiment also reveals outstanding computational and communication efficiency that outperforms current methods in tag production, proof generation, and verification. Our protocol offers an extraordinary balance of security and efficiency, making it particularly useful for auditing patent-sensitive data in multi-cloud storage. Our proposal provides a timely and effective way to protect sensitive data and prevent attackers in multi-cloud storage settings at a time when replacement attacks pose a serious concern.

Implementation of Secure Data Storage and Retrieval Approach

Implementation of a data storage and retrieval approach to achieve the best results is a challenge. The approach is proposed where access control is assured and a minimum of data information is revealed. On the other side special features of every cloud in a multi-cloud storage system make implementation more complicated. In this paper, the authors will present important problems, solutions, algorithms, comparison results, and details of the implementation of secure data storage and retrieval approach in a multi-cloudIoT system.

A Minimal-overhead Multi-cloud Data Placement Strategy Based on Heuristic Algorithm

Multi-cloud storage can provide better service levels than single cloud storage in terms of confidentiality, integrity, and availability at a low cost. More and more customers are storing data in multi-cloud storage systems. However, inefficient data placement is a challenge for multi-cloud storage, and current research has the problem of low algorithm efficiency. In response to this problem, a multi-cloud storage data placement optimization strategy, MPO-MO, is proposed for minimum overhead requirements. MPO-MO models availability and cost, and provides users with the lowest cost multi-cloud storage data placement strategy while meeting the specified availability constraints. A heuristic algorithm is proposed, which uses the sorting information of storage price and traffic price to select cloud storage services. According to analysis, the heuristic algorithm adopted by MPO-MO greatly reduces the optimization space compared with the traditional algorithm, and the efficiency is significantly improved. Finally, experiments prove the effectiveness of MPO-MO.

A Blockchain-Based Multi-Cloud Storage Data Auditing Scheme to Locate Faults

Network storage services have benefited countless users worldwide due to the notable features of convenience, economy and high availability. Since a single service provider is not always reliable enough, more complex multi-cloud storage systems are developed for mitigating the data corruption risk. While a data auditing scheme is still needed in multi-cloud storage to help users confirm the integrity of their outsourced data. Unfortunately, most of the corresponding schemes rely on trusted institutions such as the centralized third-party auditor (TPA) and the cloud service organizer, and it is difficult to identify malicious service providers after service disputes. Therefore, we present a blockchain-based multi-cloud storage data auditing scheme to protect data integrity and accurately arbitrate service disputes. We not only introduce the blockchain to record the interactions among users, service providers, and organizers in data auditing process as evidence, but also employ the smart contract to detect service dispute, so as to enforce the untrusted organizer to honestly identify malicious service providers. We also use the blockchain network and homomorphic verifiable tags to achieve the low-cost batch verification without TPA. Theoretical analyses and experiments reveal that the scheme is effective in multi-cloud environments and the cost is acceptable.

Research on multi-authority CP-ABE access control model in multicloud

In order to solve the problems of data sharing security and policy conflict in multicloud storage systems (MCSS), this work designs an attribute mapping mechanism that extends ciphertext policy attribute-based encryption (CP-ABE), and proposes a multi-authority CP-ABE access control model that satisfies the need for multicloud storage access control. The mapping mechanism mainly involves the tree structure of CP-ABE and provides support for the types of attribute values. The framework and workflow of the model are described in detail. The effectiveness of the model is verified by building a simple prototype system, and the performance of the prototype system is analyzed. The results suggest that the proposed model is of theoretical and practical significance for access control research in MCSS. The CP-ABE has better performance in terms of computation time overhead than other models.

Dew Computing and Asymmetric Security Framework for Big Data File Sharing

Due to the advancement of technology, devices generate huge working files at a rapid rate. These data, which are of considerable scale and are created very fast, can be called big data. Keeping such files in one storage device is impossible. Therefore, a large file size is recommended for storage in a cloud storage service. Although this concept is a solution to solve the storage problem, it still faces challenges in terms of reliability and security. The main issues are the unreliability of single cloud storage when its service is down, and the risk of insider attack from the storage service. Therefore, this paper proposes a file sharing scheme that increases both the reliability of the file fragments using a multi-cloud storage system and decreases the risk from insider attack. The dew computing concept is used as a contributor to the file-sharing scheme. The working file is split into fragments. Each fragment is deployed to cloud storage services, one fragment per one cloud provider manner. The dew server controls users’ access and monitors the availability of fragments. Finally, we verify the proposed scheme in aspects of the downloading performance, and security.

Data Consistency in Multi-Cloud Storage Systems With Passive Servers and Non-Communicating Clients

Multi-cloud storage systems are becoming more popular due to the ever-expanding amount of consumer data. This growth is accompanied by increasing concerns regarding security, privacy, and reliability of cloud storage solutions. Ensuring data consistency in such systems is especially challenging due to their architecture and characteristics. Specifically, passive cloud storage cannot run coordination software, and clients cannot communicate directly to reach consensus. Furthermore, the atomicity of operations is not always guaranteed by the clouds' public APIs. In this paper, we formally define data consistency in multi-cloud storage systems, identify how they can be violated, and introduce a new method that provably maintains the data consistency in these systems. The implementation and experiments show that the proposed method can maintain data consistency with a certain delay in data uploading and that it is scalable with respect to the number of used clouds as well as the number of users. Integrating this method into multi-cloud storage systems will enhance their usability and reliability.

Towards Hybrid Multi-Cloud Storage Systems: Understanding How to Perform Data Transfer

Abstract Nowadays, storing and retrieving information over the Cloud is critical for the survival and growth of organizations and people. In this context, the possibility to store a huge amount of data and files on remote third-party Cloud storage providers is becoming an even more concrete practice. Unfortunately, there is not any guarantee regarding data availability and reliability of such providers. In such a context, if the Cloud wants to use the storage as a service of another Cloud, it has only to trust it. A possible solution consists of using a Multi-Cloud Storage (MCS) system. However, how organizations should compose their own MCS system on geo-distribution basis is not trivial at all. In this paper, we specifically discuss how to optimize the overall system in terms of data storage and retrieval by testing and validating a MCS system composed of three major Cloud Storage providers; Dropbox, Google Drive and Copy. Experiments have proved that the choice of the Cloud storage providers where to store files depends on the data transfer performance according to the file chunk size. In addition, we demonstrated that not always the provider that offers the best performance in upload also offers the best performance in download.

A Novel Approach for Multi-Cloud Storage for Mobile Devices

Regardless of high embracing rate among users, Multi Cloud Storage Systems for mobile devices still have many limitations. From recent studies, it is clear that multi cloud storage systems work well for desktop PCs where there is no resource limitation but when accessed on mobile devices, these systems consumed a lot of resources of the mobile device. In this article, the authors reviewed three multi cloud storage systems for mobile devices ES File Explorer, Mult Cloud, Otixo and evaluate their performance on the basis of parameters Battery Consumption, CPU Usage, and Data Usage on Jio-Fi network using two mobile devices Micromax Canvas E352 and Redmi Note 4. Then, the authors propose an approach for multi cloud storage for mobile devices that will remove the limitations of previously discussed systems.

MWC: an efficient and secure multi-cloud storage approach to leverage augmentation of multi-cloud storage services on mobile devices using fog computing

To store the sensitive and large amount of information on mobile devices is not recommended as it can be lost or stolen and the storage capacity is limited. Even the services of the single-cloud storage provider are not preferred due to issues like limited free storage, vendor lock-in and data loss. To deal with these issues, multi-cloud storage services are preferred which provide a single platform for multiple cloud storage services. From recent studies, it has been observed that the use of existing multi-cloud storage systems is uncommon by mobile users because they have lots of issues when accessed through resource-constrained mobile devices as they are consuming a lot of resources like CPU, battery and data (Internet usage) of mobile devices. So, in this paper, an efficient and secure multi-cloud storage approach is developed using the concept of fog computing to leverage augmentation of multi-cloud storage services on resource-constrained mobile devices.

Multi-cloud storage systems for mobile devices: study and analysis

Despite high demand of smart mobile devices among users as in case of mobile learning, it has a lot of issues as limited storage capacity, processing power and battery backup. Recent studies described that these limitations can be removed by using the concept of mobile cloud computing. There are many multi-cloud storage systems for mobile devices having different features and limitations. In this article, we are providing study and analysis of three multi-cloud storage systems for mobile devices named Mult Cloud, ES File Explorer and Cloud Cube and evaluate their performance on the basis of CPU usage, battery consumption, time consumption and data usage parameters on Wi-Fi network and using two mobile phones, Sony Xperia ZL smart phone and Nexus 7 tablet. Finally, open research challenges and future scope are discussed.

Multi-cloud storage systems for mobile devices: study and analysis

Despite high demand of smart mobile devices among users as in case of mobile learning, it has a lot of issues as limited storage capacity, processing power and battery backup. Recent studies described that these limitations can be removed by using the concept of mobile cloud computing. There are many multi-cloud storage systems for mobile devices having different features and limitations. In this article, we are providing study and analysis of three multi-cloud storage systems for mobile devices named Mult Cloud, ES File Explorer and Cloud Cube and evaluate their performance on the basis of CPU usage, battery consumption, time consumption and data usage parameters on Wi-Fi network and using two mobile phones, Sony Xperia ZL smart phone and Nexus 7 tablet. Finally, open research challenges and future scope are discussed.

Design and implementation of an efficient multi cloud storage approach for resource constrained mobile devices

In todays scenario of Big Data, to reduce data management and maintenance cost, many companies and users starts shifting their data to cloud. To store or access data from remote storage (cloud storage) by using a desktop device as PC is not a problem but as the demand of smart mobile devices is increases day by day as compared to desktop devices if user want to store or retrieve data from cloud storage using these mobile devices, it will consume a lot of resources of mobile device. Which is the main issue as mobile devices have limited resources as battery, CPU, memory, etc. To deal with the free limited storage issue, a lot of multi cloud storage systems are available but none of them is capable to save resources of mobile devices as battery, CPU and data (Internet) usage. So there is a need of an efficient multi cloud storage approach that will consume fewer resources of mobile devices. In this paper, we are proposing design and implementation of an efficient multi cloud storage approach for resource constrained mobile devices that will consume fewer resources of mobile devices and give better results in terms of battery consumption, CPU usage and data usage.

Hybris

Besides well-known benefits, commodity cloud storage also raises concerns that include security, reliability, and consistency. We present Hybris key-value store, the first robust hybrid cloud storage system, aiming at addressing these concerns leveraging both private and public cloud resources. Hybris robustly replicates metadata on trusted private premises (private cloud), separately from data, which are dispersed (using replication or erasure coding) across multiple untrusted public clouds. Hybris maintains metadata stored on private premises at the order of few dozens of bytes per key, avoiding the scalability bottleneck at the private cloud. In turn, the hybrid design allows Hybris to efficiently and robustly tolerate cloud outages but also potential malice in clouds without overhead. Namely, to tolerate up to f malicious clouds, in the common case of the Hybris variant with data replication, writes replicate data across f +1 clouds, whereas reads involve a single cloud. In the worst case, only up to f additional clouds are used. This is considerably better than earlier multi-cloud storage systems that required costly 3 f +1 clouds to mask f potentially malicious clouds. Finally, Hybris leverages strong metadata consistency to guarantee to Hybris applications strong data consistency without any modifications to the eventually consistent public clouds. We implemented Hybris in Java and evaluated it using a series of micro and macro-benchmarks. Our results show that Hybris significantly outperforms comparable multi-cloud storage systems and approaches the performance of bare-bone commodity public cloud storage.

CloudS: A Multi-Cloud Storage System with Multi-Level Security

With the increase of data quantity, people have begun to attach importance to cloud storage, however, traditional single cloud can’t ensure the privacy of users’ data to a certain extent. To solve the security issue, we present a multi-cloud storage system called CloudS which spreads data over multiple cloud storage servers by using a new kind of XOR-based non-systematic erasure codes - Privacy Protecting Codes (PPC). For better user experiences and tradeoffs between security and performance, CloudS provides multiple levels of security by a variety of combinations of compression, encryption and coding schemes. In addition, we also put forward a novel Parallel Cyclic Encryption (PCE) scheme to achieve random secret key protection which attains high security and performance. We implement CloudS as a web application which doesn’t require users to perform complicated operations on local.

Design and Implement Enhancing Security in Multi Cloud Storage System using Distributed File System

Distributed computing is a quickest developing engineering. It permits business associations to utilize or access diverse applications, store data without access their individual documents. While considering the force, strength and the security of cloud one can't disregard diverse dangers to client's information on distributed storage. Document access guarantee in true procedure to the record assurance because of entrust cloud servers. In distributed storage framework document doorway system is all the more difficult issue. This framework in result produces repetitive duplicates of comparative documents or includes a totally dependable cloud server. Assaults from enemy client are hard to stop in distributed storage. In proposed framework we are actualizing the idea of various distributed storage alongside improved security utilizing encryption strategies where rather putting away finish record on single cloud framework. The framework will part the record in distinctive lumps then encode it and store on diverse cloud. The information needed for unscrambling and revamping that document will be put away in metadata administration server for effective recovery of unique record.

Adding long-term availability, obfuscation, and encryption to multi-cloud storage systems

Nowadays, storage services offer a new way for Cloud providers to do business. This new trend is proved by the number of Cloud storage providers that are continuously appearing on the market. By now, using Cloud storage services is becoming a common practice for end-users. However, the current Cloud storage providers do not offer any guarantees regarding long-term availability and privacy. In fact, data stored in the Cloud could be locked-in, lost, or violated in terms of privacy. In this work, we present an innovative system that on one hand allows end-users to simultaneously rely on different Cloud storage providers in a transparent way and on the other hand to enforce long-term availability, obfuscation, and encryption. Our system is highly reliable, in fact, if a provider is not temporarily or permanently available, end-users continue accessing their data in a secure way. In addition, only the end-users have the full control of the overall security of their data and no sensitive information are disclosed to Cloud storage providers. Several experiments allow us to discuss the performance of our system compared against existing solutions.