Workload models and performance evaluation of cloud storage services

The advent of the cloud era has yielded new ways of storing, accessing and managing data. Cloud storage services enable the storage of data in an inexpensive, secure, fast, reliable and highly scalable manner over the internet. Although giant providers such as Amazon and Google have made a great success of their services, many enterprises and scientists are still unable to make the transition into the cloud environment due to often insurmountable issues of privacy, data protection and vendor lock-in. These issues demand that it be possible for anyone to setup or to build their own storage solutions that are independent of commercially available services. However, the question persists as to how to provide an effective cloud storage service with regards to system architecture, resource management mechanisms, data reliability and durability, as well as to provide proper pricing models. The aim of this research is to present an in-depth understanding and analysis of the key features of generic cloud storage services, and of how such services should be constructed and provided. This is achieved through the demonstration of design rationales and the implementation details of a real cloud storage system (CACSS). The method by which different technologies can be combined to provide a single excellent performance, highly scalable and reliable cloud storage system is also detailed. This research serves as a knowledge source for inexperienced cloud providers, giving them the capability of swiftly setting up their own cloud storage services.

With the rapid development of networks and Information technologies, cloud computing is not only becoming popular, the types of cloud services available are also increasing. Through cloud services, users can upload their requirements via the Internet to the cloud environment and receive responses following post-processing, for example, with cloud storage services. Software-Defined Storage (SDS) is a virtualization technology for cloud storage services. SDS uses software to integrate storage resources and to improve the accessibility and usability of storage services. Currently, there are many different open source projects available for SDS development. This work aims to utilize these open source projects to improve the efficiency of integration for hardware and software resources. In other words, in this work, we propose a cloud storage system that integrates various open source SDS software to make cloud storage services more compatible and user friendly. The cloud service systems can also be managed in a more convenient and flexible manner. The experimental results demonstrate the benefits of the proposed 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.

While we can now outsource data backup to third-party cloud storage services so as to reduce data management costs, security concerns arise in terms of ensuring the privacy and integrity of outsourced data. We design FADE, a practical, implementable, and readily deployable cloud storage system that focuses on protecting deleted data with policy-based file assured deletion. FADE is built upon standard cryptographic techniques, such that it encrypts outsourced data files to guarantee their privacy and integrity, and most importantly, assuredly deletes files to make them unrecoverable to anyone (including those who manage the cloud storage) upon revocations of file access policies. In particular, the design of FADE is geared toward the objective that it acts as an overlay system that works seamlessly atop today’s cloud storage services. To demonstrate this objective, we implement a working prototype of FADE atop Amazon S3, one of today’s cloud storage services, and empirically show that FADE provides policy-based file assured deletion with a minimal trade-off of performance overhead. Our work provides insights of how to incorporate value-added security features into current data outsourcing applications.

Cloud Storage Forensics

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.

Since the popularity of the Internet, more and more people have chosen to look for the information and resources they need on the Internet. People’s lives have gradually been changed by the Internet. Cloud storage brings new development opportunities, and the copyright protection issues involved in cloud storage are gradually emerging. Cloud storage has changed the original pattern among traditional information owners, disseminators and users, causing conflicts among copyright owners, cloud storage servers and information acquirers, and the problem of copyright protection has become increasingly prominent. The rapid development of network file sharing platforms such as cloud storage brings unprecedented challenges to copyright protection. The application and development of cloud storage also challenges the recognition of traditional copyright system, object and content, so we must balance the contribution of cloud storage to the exchange of information resources and protect the legitimate rights and interests of copyright holders.

Deduplication is an important technology in the cloud storage service. For protecting user privacy, sensitive data usually have to be encrypted before outsourcing. This makes secure data deduplication a challenging task. Although convergent encryption is used to securely eliminate duplicate copies on the encrypted data, these secure deduplication techniques support only exact data deduplication. That is, there is no tolerance of differences in traditional deduplication schemes. This requirement is too strict for multimedia data including image. For images, typical modifications such as resizing and compression only change their binary presentation but maintain human visual perceptions, which should be eliminated as duplicate copies. Those perceptual similar images occupy a lot of storage space on the remote server and greatly affect the efficiency of deduplication system. In this paper, we first formalize and solve the problem of effective fuzzy image deduplication while maintaining user privacy. Our solution eliminates duplicated images based on the measurement of image similarity over encrypted data. The robustness evaluation is given and demonstrates that this fuzzy deduplication system is able to duplicate perceptual similar images, which optimizes the storage and bandwidth overhead greatly in cloud storage service.

The utilization of "cloud storage services (CSS)", empowering people to store their data in cloud and avoid from maintenance cost and local data storage. Various data integrity auditing (DIA) frameworks are carried out to ensure the quality of data stored in cloud. Mostly, if not all, of current plans, a client requires to utilize his private key (PK) to generate information authenticators for knowing the DIA. Subsequently, the client needs to have hardware token to store his PK and retain a secret phrase to actuate this PK. In this hardware token is misplaced or password is forgotten, the greater part of existing DIA plans would be not able to work. To overcome this challenge, this research work suggests another DIA without "private key storage (PKS)"plan. This research work utilizes biometric information as client's fuzzy private key (FPK) to evade utilizing hardware token. In the meantime, the plan might in any case viably complete the DIA. This research work uses a direct sketch with coding and mistake correction procedures to affirm client identity. Also, this research work plan another mark conspire that helps block less. Verifiability, yet in addition is viable with linear sketch Keywords– Data integrity auditing (DIA), Cloud Computing, Block less Verifiability, fuzzy biometric data, secure cloud storage (SCS), key exposure resilience (KER), Third Party Auditor (TPA), cloud audit server (CAS), cloud storage server (CSS), Provable Data Possession (PDP)

Cloud Storage Service (CSS) is a vital service of cloud computing which relieves the burden of storage management, cost and maintenance. However, Cloud storage introduces new security and privacy challenges that make data owners worry about their data. It is essential to have an auditing service to verify the integrity of outsourced data and to prove to data owners that their data is correctly stored in the Cloud. Recently, many researchers have focused on validating the integrity of outsourced data and proposed various schemes to audit the data stored on CSS. However, most of those schemes deal with static and single copy data files and do not consider data dynamic operations on replicated data. Furthermore, they do not have the facility to repair corrupt data. In this paper, we address these challenging issues and propose a public auditing scheme for multiple-copy outsourced data in CSS. Our scheme achieves better reliability, availability, and scalability by supporting replication and data recovery.Keywordscloud storageauditingprobabilistic encryptionfountain codescryptographic hash algorithms

Using cloud data clients may transfer data from their computer systems to cloud servers. Hence, user will not have any burden of maintenance and also he gets high quality data storage services. Many security issues are concerned with cloud storage. Cloud service providers or storage servers are not completely trustworthy. The user is concerned about the information stored on cloud are in place or not turns. This paper is based on homomorphic hash algorithm. Further this supports dynamic operations such as insert, update, delete and modify at block level, for data dynamics Merkle Hash Tree is used which helps to find the location of each dynamic operation. Third party auditor checks the user's data for correctness and gives the accuracy of the data that is stored in cloud server. The communication and computation overhead are reduced. Deduplication technique is used to check whether the file that user need to store in cloud storage is already exist at cloud server or not. This framework is effective and secure against replace attack launch by malicious server.

In companies internal communication, most staff will use penetration of high communication tools such as QQ, Wechat. Most of this kind of communication tools are based on AES, RSA, encryption process handled by the backend server, Such software can view the messages and files sent and transferred by users, but within the confidential file cannot allow the situation to exist. In view of the appeal, the data protection system, namely fine granularity permission management, is proposed. On this basis, an application tool integrating encryption decentralized real-time communication and data security storage is realized. This system is based on the Django framework to complete the construction of communication, storage function, this system is mainly divided into two modules, the first module is decentralized encryption communication module, the proposed system provides identity authentication function, user decentralized encryption real-time communication, to ensure the communication information is not outside the attacker or system developers to obtain; The second module is cloud storage service module, cloud storage technology as the core, for file transfer of decentralized communication and data storage services, and cloud storage in the database files will be combined with fine granularity rights management function, the user can undertake the level set to other users and one-way level set of file, In this way, you can control the range of files in the cloud storage database. Based on blockchain technology, blockchain will replace traditional third-party servers, so as to complete decentralized integrity authentication. In this system, encryption-related content will not be generated by the back-end server, and key information and other important information will not enter the database based on the idea of decentralization, while ciphertext transmission and encrypted ciphertext information storage are provided by the cloud storage server. Based on the idea of decentralization, this system can be completed under the circumstance that the data is not leaked when the cloud database is invaded. All the encryption algorithms of the system use the national secret algorithm to achieve decentralized secure real-time communication, integrity authentication and fine granularity permission management.

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.

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.