Users’ Payment Intention considering Privacy Protection in Cloud Storage: An Evolutionary Game-Theoretic Approach

To solve the current privacy leakage problems of cloud storage services, research on users’ payment intention for cloud storage services with privacy protection is extremely important for improving the sustainable development of cloud storage services. An evolutionary game model between cloud storage users and providers that considers privacy is constructed. Then, the model’s evolutionary stability strategies via solving the replication dynamic equations are analyzed. Finally, simulation experiments are carried out for verifying and demonstrating the influence of model parameters. The results show that the evolutionary stable strategies are mainly affected by the privacy protection profit growth coefficient of both parties, input costs, free-riding gains, and other factors. If the profit growth coefficient is very small, users will not choose to pay and providers will not choose to actively protect user information. As the profit growth coefficient increases, both parties will promote the development of privacy protection with a higher probability. The results are beneficial for cloud storage providers to increase the number of paid users and thus to achieve the sustainable development of cloud storage service.

Detailed Study of Cloud Storage Services on Aws Cloud (Amazon Web Services)

This research revolves around understanding the Cloud Storage Services offered by world's most famous Cloud Provider Amazon Web Services (AWS). We will be covering major Cloud Storage Services like EBS, S3 and EFS. But first let’s understand more about AWS. We should use these end-of-life services as a per-project and keep in mind the key benefits of these end-to-end services. Amazon EBS brings the highest end-to-end prices available with block for level of Amazon Elastic Compute Cloud (EC2) instances. Saves data to file system stored after EC2 status closure. Amazon EFS provides portable file storage, also designed for EC2. It can be used as a standard data source for any application or load that works in most cases. Using the EFS file system, you can configure file system installation settings. The main difference between EBS and EFS is that EBS is only accessible from a single EC2 state in your specific AWS region, while EFS allows you to mount a file system in multiple regions and scenarios.

Secure Symmetric Keyword Search with Keyword Privacy for Cloud Storage Services

As Internet services are widely used in various mobile devices, the amount of data produced by users steadily increases. Meanwhile, the storage capacity of the various devices is limited to cover the increasing amount of data. Therefore, the importance of Internet-connected storage that can be accessed anytime and anywhere is steadily increasing in terms of storing and utilizing a huge amount of data. To use remote storage, data to be stored need to be encrypted for privacy. The storage manager also should be granted the ability to search the data without decrypting them in response to a query. Contrary to the traditional environment, the query to Internet-connected storage is conveyed through an open channel and hence its secrecy should be guaranteed. We propose a secure symmetric keyword search scheme that provides query privacy and is tailored to the equality test on encrypted data. The proposed scheme is efficient since it is based on prime order bilinear groups. We formally prove that our construction satisfies ciphertext confidentiality and keyword privacy based on the hardness of the bilinear Diffie–Hellman (DH) assumption and the decisional 3-party DH assumption.

AI - Based Framework for Private Cloud Computing

Artificial Intelligence (AI) systems are computational simulations that are "trained" using information and expert input to duplicate a professional's choice given the same data. Only using one private cloud storage service to store information can cause a variety of issues for the system administrator. Knowledge providers, scalability, efficiency, privacy, and the potential of vendor support are examples of such concerns. Distributing information across several cloud storage services, comparable to how data is dispersed between various physical disk drives to increase error detection and increase productivity, is a possible approach. Moreover, because multiple private cloud providers have varying pricing strategies and service quality, maximizing the efficiency and profitability of many cloud providers at the same time is difficult. Based on access permission behaviors, this study presents a methodology for dynamically modifying network management rules across several cloud providers. The goal of this research is to look into how to reduce both the estimated cost and delay periods for numerous cloud providers. The architecture was put into practice in a cloud storage systems emulator, which simulated the complexity and effectiveness of numerous cloud providers in a real-world context. In particular, the architecture was evaluated in a variety of cloud storage environments. The outcomes of the platform's testing revealed that many cloud methods were successful.

Protecting the Sharing and Distribution of Color Images Hosted in Cloud Storage Services

In recent years, the reversible data hiding techniques also known as lossless or invertible data hiding, has gradually become a very active research area. The reversibility of these schemes makes possible to extract the embedded data without errors, as well as to restore the cover medium to its original state. Furthermore, to guarantee the security and confidentiality of the hidden data and the image, reversible data hiding schemes over encrypted domain are presented as a promising solution to solve several issues of information security. This paper presents a study case of reversible data hiding schemes over encrypted domain oriented to the protection of the sharing and distribution of color images hosted in cloud storage services. The experimental results are presented in terms of imperceptibility, capacity, confidentiality, and visual quality, respectively.

Designing High Availability Cluster Using Server Virtualization on Cloud Storage Services

Cloud Storage Service at PT. Harrisma Globaltechnologies Jakarta has not been applied based on virtualization. The problem with cloud storage services in general is that the server is not able to serve a high number of requests as a result the cloud storage server fails. One of these problems is caused by inadequate server resources and less than optimal storage server management. These problems can be solved effectively and efficiently with server virtualization. Where server virtualization is managed by Proxmox. Proxmox is an open-source virtualization platform supported by KVM and OpenVZ hypervisors and can be managed with web-based graphics. Server virtualization collaboration can save server resources by duplicating server services virtually. The research methodology used is clustering by applying the concept of high-availability where there is a secondary server as a backup-server for the primary-server. The results of this study include three parameters, namely Throughput, Response Time, and CPU Usage. The results show that cloud storage servers that implement virtualization than those that do not apply with a difference in the value of the Throughput parameter of 1896.6 Kbps, the difference in the value of the Response Time parameter of 10.6 requests/second, and the difference in the value of the CPU Usage criteria of 11.91%

User Privacy Protection Scheme Based on Verifiable Outsourcing Attribute-Based Encryption

Given the rapid development of cloud computing and cloud storage technology, a growing number of enterprises and individuals use cloud storage services to save data or back up data. In the cloud storage services, although attribute-based encryption can protect users’ data security, the computational cost of key generation, data encryption, and data decryption linearly increases with the complexity of access strategies, which becomes more critical for resource-constrained users. Therefore, this paper proposes a verifiable attribute-based encryption scheme for a fully outsourced ciphertext policy. The scheme can simultaneously realize the functions of key generation, data encryption, and data decryption outsourcing and verify the correctness of the outsourcing calculation results. This scheme can effectively reduce the computational burden of a cloud storage system. The security and verifiability of the scheme are indicated and proved with the random oracle model. The experimental results show that the scheme has the advantages of function and efficiency compared with other schemes. The research results have theoretical and practical significance.

Validation of Architecture Effectiveness for the Continuous Monitoring of File Integrity Stored in the Cloud Using Blockchain and Smart Contracts

The management practicality and economy offered by the various technological solutions based on cloud computing have attracted many organizations, which have chosen to migrate services to the cloud, despite the numerous challenges arising from this migration. Cloud storage services are emerging as a relevant solution to meet the legal requirements of maintaining custody of electronic documents for long periods. However, the possibility of losses and the consequent financial damage require the permanent monitoring of this information. In a previous work named “Monitoring File Integrity Using Blockchain and Smart Contracts”, the authors proposed an architecture based on blockchain, smart contract, and computational trust technologies that allows the periodic monitoring of the integrity of files stored in the cloud. However, the experiments carried out in the initial studies that validated the architecture included only small- and medium-sized files. As such, this paper presents a validation of the architecture to determine its effectiveness and efficiency when storing large files for long periods. The article provides an improved and detailed description of the proposed processes, followed by a security analysis of the architecture. The results of both the validation experiments and the implemented defense mechanism analysis confirm the security and the efficiency of the architecture in identifying corrupted files, regardless of file size and storage time.