Multi - owner Secure Data Sharing in Cloud Computing Environment

Data sharing in the cloud is a technique that allows users to conveniently access data over the cloud. The data owner outsources their data in the cloud due to cost reduction and the great conveniences provided by cloud services. Data owner is not able to control over their data, because cloud service provider is a third party provider.  The main crisis with data sharing in the cloud is the privacy and security issues. Various techniques are available to support user privacy and secure data sharing. This paper focus on various schemes to deal with secure data sharing such as Data sharing with forward security, secure data sharing for dynamic groups, Attribute based data sharing, encrypted data sharing and Shared Authority Based Privacy-Preserving Authentication Protocol for access control of outsourced data

Encryption Based Access Control Model In Cloud: A Survey

Cloud computing is known as “Utility”. Cloud Computing enabling users to remotely store their data in a server and provide services on-demand. Since this new computing technology requires user to entrust their valuable data to cloud providers, there have been increasing security and privacy concerns on outsourced data. We can increase security on access of the data in the cloud. Morever we can provide encryption on the data so third party can not use thedata. In this paper we will be reviewing various encryption based access control model for enhancing cloud security along with their limitations. We will be concluding with a proposed access control model to enhance cloud security

Enabling Data Security and Privacy for Database Services in the Cloud

Substantial advances in cloud technologies have made outsourcing data to the cloud highly beneficial today (e.g., costs savings, scalability, provisioning time). However, strong concerns from private companies and public institutions about the security of the outsourced data still hamper the adoption of cloud solutions. This reluctance is fed by frequent massive data breaches either caused by external attacks against cloud service providers or by negligent or opaque practices from the service provider itself. For broader adoption of cloud services, this dissertation addresses the data security and privacy concerns in the cloud setting. The goal is to ensure security and privacy of outsourced data while maintaining the ability to execute queries efficiently. Security/privacy comes at a cost of functionality/performance. Therefore, we seek for a proper balance in the space of security, privacy, functionality, and performance. This dissertation works the problems of range query execution over encrypted data, privacy preserving data mining in the context of environmental sustainability studies, and access privacy in the cloud. To enable efficient and secure range query processing over traditional databases, we introduce PINED-RQ, a highly efficient and differentially private range query execution framework that constructs a novel differentially private index over an outsourced database. Second, this dissertation presents a comprehensive study of the environmental sustainability metrics. Our contributions in this context are twofold: 1) to better evaluate the environmental impacts of the industrial processes privately, we formally define privacy preserving certification paradigm and develop a framework that enables untrusted third party to certify parties based on a well agreed upon set of criteria. 2) to explore the privacy concerns over publicizing the industrial activities in the form of life cycle assessment (LCA) computations, which is a standard way of evaluating an impact of a product and service. This dissertation initiates a study to explore privacy and security challenges that prevent organizations from making public disclosures about their activities. Finally, this dissertation explores access privacy in the cloud setting. We design and develop TaoStore, a highly efficient and practical cloud data store, which secures data confidentiality and hides access patterns from adversaries. Additionally, we propose a new ORAM security model, called aaob-security, which considers completely asynchronous network communication and concurrent processing of requests. This dissertation shows that it is possible to deliver practical and high-performance data services in the cloud without sacrificing securityand privacy if the requirements of each application are analyzed correctly and a correct balance is found in the space of security, privacy, functionality, and performance

MIGRATING DATA TO THE CLOUD: AN ANALYSIS OF CLOUD STORAGE PRIVACY AND SECURITY ISSUES AND SOLUTIONS

The rise of a digital economy has transformed how individuals do business and carry out daily tasks, including how data is maintained. Because of the vast amount of data that organizations own, cloud storage, a component of the cloud computing paradigm, has emerged as a feasible solution to many businesses\u27 data storage concerns. Despite this, organizations are still cautious about moving all of their data to the cloud due to security concerns, particularly since data management is outsourced to third parties. The aim of this paper is to provide an overview of current challenges in the field of cloud storage privacy and security, with an emphasis on issues related to data confidentiality, integrity, and availability. Using a comprehensive literature study, this research investigates innovative strategies for creating a secure cloud storage environment. The idea of maintaining privacy and data security through the very design of the services, or through the so-called "privacy by design" approach, is explained while avoiding getting into the technical details of how the algorithms and presented solutions work