A fountain codes-based hybrid P2P and cloud storage system

In the HDFS cloud storage environment, the existing replica strategy is not able to adopt the optimal replica according to the current system environment dynamically, which affects the performance of the Cloud Storage system. This paper aims at the replica selection strategies in the load balancing problem, proposes a Replica Strategy based on grey prediction theory in Cloud Storage and predicts the node load rate of different replicas at a moment, selecting the minimum load node dynamically, eventually to load balance.

Today more and more enterprises and individuals are outsourcing their data to cloud storage system. Data deduplication is one of the important technologies to reduce the storage cost of cloud storage system. In a cloud storage system with deduplication technology, the client can outsource the data files to the cloud storage server and pay for them. Fair payment is one of key issues in the cloud deduplication storage system. At present, a variety of secure deduplication encryption schemes have been designed to protect the privacy of client data. However, most existing fair payment solutions use traditional electronic cash systems to generate payment tokens, which requires a trusted authority to prevent double-spending. Trusted authorities will become bottlenecks in the payment system. Faced with this problem, in this paper, we propose a new decentralized fair payment protocol for cloud deduplication storage system by utilizing ethereum blockchain technology. The new protocol takes advantage of the decentralization of blockchain technology, allowing direct transactions without the participation of trusted third parties. In the new protocol, if a malicious situation occurs, the system can guarantee fair payment by pre-storing penalty money in the smart contract. Safety analysis and experimental analysis show that our new protocol is feasible.

With the continuous development of Internet technology, cloud storage has been widely applied and developed. Users can store data through the network anytime, anywhere. However, the frequent occurrence of a series of cloud storage data security events show that cloud storage not only provides data storage services for users, but also poses huge threats and challenges to users' data security. Aiming at the problem of user data security in cloud storage environment, the system introduces multi-cloud storage system on the basis of the traditional single cloud storage system. The system uses Erasure Code to block the original data, and encrypts the data blocks using AES (Advanced Encryption Standard) encryption technology, then stores the encrypted data blocks in different cloud storages terminals. Thus, the hidden danger of data loss or leakage due to relying on a cloud service provider is eliminated, the existing security problems of cloud storage system are improved, and the security and reliability of the multi-cloud secure storage system are improved.

Multi-authority proxy re-encryption based on CPABE for cloud storage systems

The new development trends including Internet of Things (IoT), smart city, enterprises digital transformation and world's digital economy are at the top of the tide. The continuous growth of data storage pressure drives the rapid development of the entire storage market on account of massive data generated. By providing data storage and management, cloud storage system becomes an indispensable part of the new era. Currently, the governments, enterprises and individual users are actively migrating their data to the cloud. Such a huge amount of data can create magnanimous wealth. However, this increases the possible risk, for instance, unauthorized access, data leakage, sensitive information disclosure and privacy disclosure. Although there are some studies on data security and privacy protection, there is still a lack of systematic surveys on the subject in cloud storage system. In this paper, we make a comprehensive review of the literatures on data security and privacy issues, data encryption technology, and applicable countermeasures in cloud storage system. Specifically, we first make an overview of cloud storage, including definition, classification, architecture and applications. Secondly, we give a detailed analysis on challenges and requirements of data security and privacy protection in cloud storage system. Thirdly, data encryption technologies and protection methods are summarized. Finally, we discuss several open research topics of data security for cloud storage.

More and more embedded devices, such as mobile phones, tablet PCs and laptops, are used in every field, so huge files need to be stored or backed up into cloud storage. Optimizing the performance of cloud storage is very important for Internet development. This paper presents the performance evaluation of the open source distributed storage system, a highly available, distributed, eventually consistent object/blob store from OpenStack cloud computing components. This paper mainly focuses on the mechanism of cloud storage as well as the optimization methods to process different sized files. This work provides two major contributions through comprehensive performance evaluations. First, it provides different configurations for OpenStack Swift system and an analysis of how every component affects the performance. Second, it presents the detailed optimization methods to improve the performance in processing different sized files. The experimental results show that our method improves the performance and the structure. We give the methods to optimize the object-based cloud storage system to deploy the readily available storage system.

Data redundancy consumes huge storage space while setting up or employing cloud and fog storage. The dynamic cloud nature primarily focuses on the static environments which must be revised. Data deduplication solutions help minimize and control this issue by eradicating duplicate data from cloud storage systems. Since it might improve storage economy and security, data deduplication (DD) over encrypted data is a crucial problem in computing and storage systems. In this research, a novel approach to building secure deduplication systems across cloud and fog environments is developed. It uses MCDD and convergent cryptographic algorithms. The two most significant objectives of such systems are the focus of the suggested approach. Data redundancy must be minimized, but it also needs to be secured using a robust encryption method, which needs to be devised. The suggested approach is ideally suited for tasks like a user uploading new data to cloud storage or the fog. The proposed method might eliminate data redundancy by detecting redundancy at the block level. The testing results indicate that the recommended methodology can surpass a few cutting-edge techniques regarding computing effectiveness and security levels. The file is encrypted twice, once with the modified cryptographic model for deduplication (MCDD) and once with convergence encryption (CE).

Cloud storage is an indispensable part of cloud computing solutions and the security of its stored data has become a key issue in the research and application of cloud storage systems. To solve this problem, this paper studies the anti-eavesdropping regenerating code technology for cloud storage systems, from the perspective of information theory. As opposed to the existing research ideas on regenerating code theory, that enable the system to obtain strong/weak security, this paper focuses on quantifying the relationship between security and system performance parameters, evaluating the system performance gains that can be obtained by appropriately reducing security, and designing regenerating code schemes with different information security levels to meet the personalized requirements of cloud storage customers. This paper puts forward a generalized matrix transposing method and applies it to the coding construction of fractional repetition codes. The scheme proposed in this paper will provide new ideas and methods for research on secure regenerating code technology in cloud storage systems.

A storage system in cloud is well thought-out as a very big scale storage system that has independent storage servers. The service that cloud storage provides is, that can store user's data from remote through network and other authenticated users can access the data easily. Hadoop distributed file system is used to store large files consistently and to retrieve those files at very high bandwidth to user applications. Hadoop splits the files into large blocks and distributes them amongst the nodes in the cluster. When we retrieve data from the cloud, it is very important that the computation and communication overhead should be reduced. To reduce the communication overhead the server should send only the top-n files based on the keyword when the user asks for the data files. Since the owner need not maintain the copy of the files, it is all the more necessary to make check on the files available and also check the originality of the files stored in the server periodically. In HDFS the computation is done in parallel so that the execution time is drastically reduced. In the proposed system for retrieving top-n files we use Hadoop Distributed File System, so that the search time and the communication overhead is greatly reduced.

Physical location of data in cloud storage is an increasingly urgent problem. In a short time, it has evolved from the concern of a few regulated businesses to an important consideration for many cloud storage users. One of the characteristics of cloud storage is fluid transfer of data both within and among the data centres of a cloud provider. However, this has weakened the guarantees with respect to control over data replicas, protection of data in transit and physical location of data. This paper addresses the lack of reliable solutions for data placement control in cloud storage systems. We analyse the currently available solutions and identify their shortcomings. Furthermore, we describe a high-level architecture for a trusted, geolocation-based mechanism for data placement control in distributed cloud storage systems, which are the basis of an on-going work to define the detailed protocol and a prototype of such a solution. This mechanism aims to provide granular control over the capabilities of tenants to access data placed on geographically dispersed storage units comprising the cloud storage.

To solve the problem of low security in cloud storage system under the background of rapid prevailing cloud technology, this paper studies the design and implementation of User Autonomous Encryption Cloud Storage System based on Dokan. With the help of Dokan's file development model, a specific file system intended for curtain group of users can be easily customized. In order to overcome the limitations existing in traditional cloud storage systems, this system manages to establish the environment with embedded AES encryption algorithms on local clients and cloud storage servers based on OpenStack. The experimental results show that the User Autonomous Encryption Cloud Storage System based on Dokan is of higher security when compared with the traditional cloud storage systems.

Cloud storage system can reshape the way how kinds of contents are generated, stored and distributed on today's Internet. It is intriguing to study the service provision of cloud storage system for the sake of providing global users with satisfactory service. This paper conducts modeling analysis of a cloud storage system, and proposes a Markov decision process modeling framework to analyze the reliability of the storage system. Based on the modeling analysis, the optimal strategy can be got after executing two solution algorithms. By incorporating these techniques into cloud storage system design, the authors can significantly improve the replication performance and reliability of the system in this paper. Our numerical results further demonstrate the effectiveness and superiority of our technique against traditional static approaches.

With the development of the big data era, the amount of data has entered an explosive growth phase. Limited by the constraints of cost, efficiency, and security of self-built storage systems, enterprises are forced to outsource files to cloud storage systems. However, the lack of file security and auditability in cloud storage systems continues to threaten the security of outsourced files. This paper designs and implements BFSOut, which is a secure file outsourcing method based on consortium blockchain. It uses Hyperledger Fabric and Interplanetary File System (IPFS) as the underlying storage engine, which solves the problem of cloud storage security issues. In BFSOut, in order to ensure the security of outsource files, the client-side offline block encryption is used. Furthermore, a dynamic hybrid encryption scheme is adopted, making the overall encryption effect more Efficient. Experimental performance analysis show that the system has good performance.

In order to improve the efficiency of teaching resource integration, this paper designs an English multimedia network teaching resource integration system based on cloud storage. The hardware design completes the design of FPGA core board and the selection design of embedded microprocessor. In the software part, the functional module architecture of cloud storage system and the multimedia network resource integration database under cloud storage system are designed. The test results show that compared with the English teaching resource integration system without cloud storage test group, the coupling coefficient of the resource integration system designed in this paper is relatively high. It shows that the system has a strong ability to integrate English multimedia network teaching resources. At the same time, under the auxiliary cloud storage technology, the system has wider coverage and higher resource storage capacity, which has practical application value.

Network coding is an important cloud storage technique, which can recover data with small repair bandwidth and high reliability compared to the existing erasure coding and replication methods. However, regardless of which data recovery technique is used, the repaired data in a geographically distributed cloud storage system are easy to be eavesdropped at the transmission link between the local datacenter and its remote backup site. This kind of network security issue is called link eavesdropping in this paper. For a network coded cloud storage system, we propose a systematic design methodology to determine the important data recovery system parameters for any specified security level. Through analysis, we present the performance curves to relate the remote repair bandwidth and the number of coded data fragments. Consequently, all the important system parameters of a network coded data recovery system, including the number of storage nodes and the link capacity between the datacenter and the backup site, can be precisely designed for satisfying different security level requirements.