Design of Regenerating Code Based on Security Level in 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.

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.

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).

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.

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.

Cloud storage systems allows users to access their data from anywhere. They can download or upload their files or share them with others through the internet. Companies are competing to provide cloud storage services to users with varying features. This paper introduces criteria to compare cloud storage systems. It demonstrates the comparison between Dropbox and OneDrive in terms of their security, download/upload speed, application integration, pricing and storage, synchronization performance and focus on differences between them. The comparison conducts depend on six criteria that are: security, pricing and storage, integration of application, content sharing and synchronization. Dropbox shows the best performance in security, pricing and storage, synchronization and the download and upload of small files with small sizes. However, OneDrive shows a good performance in speed of download and upload big size of file. The comparison is intended to guide users and organizations when choose between the two services.

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

Recently, cloud computing is increasingly becoming the focus of attention at home and abroad. When the big data storage is become the core of cloud computing system, cloud computing system would evolve into a cloud storage system. With rapidly development of cloud computing, cloud storage has become one of most popular research field. HDFS (Hadoop Distributed File System) has a powerful data storage capacity for cloud storage system. However, it must be improved before applied to large scale since it exists some drawbacks during the design process. This paper researches the cloud storage model based on HDFS, solves uneven replica distribution.

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.

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.

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.

This paper proposes a general architecture of cloud storage system, analyzes the functions of the components, and discusses the key technologies, etc. Cloud storage is a novel storage service mode which the service providers supply storage capacities and data storage services through the Internet to the clients; meanwhile, the clients needn't know the details and lowered structures and mechanisms. The proposed architecture of cloud storage is layered and cooperative, and the discussed key technologies involve deployment, storage virtualization, data organization, migration, security, etc. The operation mechanism including ecology chain, game theory, ant colony optimization, data life cycle management, maintenance and update, convergence and evolution mechanisms are analyzed too. So an overall and new viewpoint to cloud storage system is illustrated.

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.

Data storage is one of the significant cloud services available to the cloud users. Since the magnitude of information outsourced grows extremely high, there is a need of implementing data deduplication technique in the cloud storage space for efficient utilization. The cloud storage space supports all kind of digital data like text, audio, video and image. In the hash-based deduplication system, cryptographic hash value should be calculated for all data irrespective of its type and stored in the memory for future reference. Using these hash value only, duplicate copies can be identified. The problem in this existing scenario is size of the hash table. To find a duplicate copy, all the hash values should be checked in the worst case irrespective of its data type. At the same time, all kind of digital data does not suit with same structure of hash table. In this study we proposed an approach to have multiple hash tables for different digital data. By having dedicated hash table for each digital data type will improve the searching time of duplicate data.

In this paper, we present a novel fountain code-based hybrid storage system that combines cloud storage with P2P storage. In the cloud storage system, all the data are consistently stored at server clusters but the data may be exposed to others accessing server clusters. On the other hand, in the P2P storage system, the data are distributed to a group of participating peers but the data retrievability may be significantly degraded. The proposed hybrid system is designed to provide the desired data retrievability with a short upload time and maintain the privacy to avoid other users from reading the contents.