Data Integrity in Multi Cloud Storage

Data integrity in cloud is became an acceptable challenge in the research community because of its vast application and usability in common people. This paper given an idea and ensure the secure and less loss in data during sharing with different user residing worldwide. We have introduced a new scheme called PDP (Provable Data Possession) scheme for distributed cloud storage to support the scalability of service and data migration. Here we have the existence of multiple cloud service providers to cooperatively store and maintain the clients’ data.   We also introduce an another scheme called  (CPDP) i.e. cooperative PDP which is based on homomorphic verifiable response and hash index hierarchy. We prove that the proposed scheme is minimizing the computational error as well as decrease the communication overhead as compare with existing methods

State of The Art and Hot Aspects in Cloud Data Storage Security

Along with the evolution of cloud computing and cloud storage towards matu- rity, researchers have analyzed an increasing range of cloud computing security aspects, data security being an important topic in this area. In this paper, we examine the state of the art in cloud storage security through an overview of selected peer reviewed publications. We address the question of defining cloud storage security and its different aspects, as well as enumerate the main vec- tors of attack on cloud storage. The reviewed papers present techniques for key management and controlled disclosure of encrypted data in cloud storage, while novel ideas regarding secure operations on encrypted data and methods for pro- tection of data in fully virtualized environments provide a glimpse of the toolbox available for securing cloud storage. Finally, new challenges such as emergent government regulation call for solutions to problems that did not receive enough attention in earlier stages of cloud computing, such as for example geographical location of data. The methods presented in the papers selected for this review represent only a small fraction of the wide research effort within cloud storage security. Nevertheless, they serve as an indication of the diversity of problems that are being addressed

Survey on securing data storage in the cloud

Cloud Computing has become a well-known primitive nowadays; many researchers and companies are embracing this fascinating technology with feverish haste. In the meantime, security and privacy challenges are brought forward while the number of cloud storage user increases expeditiously. In this work, we conduct an in-depth survey on recent research activities of cloud storage security in association with cloud computing. After an overview of the cloud storage system and its security problem, we focus on the key security requirement triad, i.e., data integrity, data confidentiality, and availability. For each of the three security objectives, we discuss the new unique challenges faced by the cloud storage services, summarize key issues discussed in the current literature, examine, and compare the existing and emerging approaches proposed to meet those new challenges, and point out possible extensions and futuristic research opportunities. The goal of our paper is to provide a state-of-the-art knowledge to new researchers who would like to join this exciting new field

Attribute Based Secured and Efficient Cloud Storage Middleware for Mobile Cloud Computing using PDP

Today handheld devices are playing more vital roles in the people�s daily lives with the fast development of wireless technology. All these devices use Internet for fetching & accessing services. Many current applications are being deployed on Cloud to save hardware & software cost. Mobile cloud has become remarkable cloud service model; in which, mobile devices are used as the information collecting and processing nodes for the cloud infrastructure. Cloud has become the pervasive digital platform for many network applications in their quest to provide a single unified digital platform. In this paper, we present insignificant Cloud-based storage framework. This framework will provide an easy-to-use file navigation service for attribute-based fill querying. Simultaneously, it incorporates an effective structure for users to verify their data integrity, which can relieve much load from mobile devices. Experimental simulations show that the proposed framework is effective to provide flexible data sharing in mobile computing environments

A Generic Dynamic Provable Data Possession Framework

Ateniese et al. introduced the Provable Data Possession (PDP) model in 2007. Following that, Erway et al. adapted the model for dynamically updatable data, and called it the Dynamic Provable Data Possession (DPDP) model. The idea is that a client outsources her files to a server, and later on challenges the server to obtain a proof that her data is kept intact. During recent years, many schemes have been proposed for this purpose, all following a similar framework. We analyze in detail the exact requirements of dynamic data outsourcing schemes regarding security and efficiency, and propose a general framework for constructing such schemes that encompasses existing DPDP-like schemes as different instantiations. We show that a dynamic data outsourcing scheme can be constructed given black-box access to an implicitly-ordered authenticated data structure (that we define). Moreover, for blockless verification efficiency, a homomorphic verifiable tag scheme is also needed. We investigate the requirements and conditions these building blocks should satisfy, using which one can easily check applicability of a given building block for dynamic data outsourcing. Finally, we provide a comparison among different building blocks

An Efficient Pdp Scheme For Distributed Cloud Storage To Support Dynamic Scalability On Multiple Storage Servers

The confirmation examination without downloading makes it particularly important for large-size files and folders typically including many clients’ files to make sure whether these data have been tampered with or deleted without downloading the latest version of data. Provable data possession is such a probabilistic proof technique for a storage provider to establish the integrity and ownership of clients’ data without downloading data. Consequently it is able to put back traditional hash and signature functions in storage outsourcing. Various PDP schemes have been recently proposed such as Scalable PDP and Dynamic PDP. Though these schemes mainly focus on PDP issues at untrusted servers in a single cloud storage provider and are not appropriate for a multi-cloud environment.  Furthermore clients need to know the exact position of each file block in a multi-cloud environment.  The confirmation process in such a case will lead to high communication overheads and calculation costs at client sides as well. Consequently it is of utmost necessary to design a cooperative PDP model to decrease the storage and network overheads and improve the transparency of verification activities in cluster-based cloud storage systems. A cooperative PDP scheme should give features for timely detecting abnormality and renewing multiple copies of data

Achieving trust-oriented data protection in the cloud environment

University of Technology, Sydney. Faculty of Engineering and Information Technology.Cloud computing has gained increasing acceptance in recent years. In privacy-conscious domains such as healthcare and banking, however, data security and privacy are the greatest obstacles to the widespread adoption of cloud computing technology. Despite enjoying the benefits brought by this innovative technology, users are concerned about losing the control of their own data in the outsourced environment. Encrypting data can resolve confidentiality and integrity challenges, but the key to mitigating users’ concerns and encouraging broader adoption of cloud computing is the establishment of a trustworthy relationship between cloud providers and users. In this dissertation, we investigate a novel trust-oriented data protection framework adapted to the cloud environment. By investigating cloud data security, privacy, and control related issues, we propose a novel data protection approach that combines active and passive protection mechanisms. The active protection is used to secure data in an independent and smart data cube that can survive even when the host is in danger. The passive protection covers the actions and mechanisms taken to monitor and audit data based on third party security services such as access control services and audit services. Furthermore, by incorporating full mobility and replica management with the active and passive mechanisms, the proposed framework can satisfy confidentiality, integrity, availability, scalability, intrusion-tolerance, authentication, authorization, auditability, and accountability, increasing users’ confidence in consuming cloud-based data services. In this work we begin by introducing cloud data storage characteristics and then analyse the reasons for issues of data security, privacy and control in cloud. On the basis of results of analysis, we identify desirable properties and objectives for protecting cloud data. In principle, cryptography-based and third party based approaches are insufficient to address users’ concerns and increase confidence in consuming cloud-based data services, because of possible intrusion attacks and direct tampering of data. Hence, we propose a novel way of securing data in an active data cube (ADCu) with smart and independent functionality. Each ADCu is a deployable data protection unit encapsulating sensitive data, networking, data manipulation, and security verification functions within a coherent data structure. A sealed and signed ADCu encloses dynamic information-flow tracking throughout the data cube that can precisely monitor the inner data and the derivatives. Any violations of policy or tampering with data would be compulsorily recorded and reported to bundled users via the mechanisms within the ADCu. This active and bundled architecture is designed to establish a trustworthy relationship between cloud and users. Subsequently, to establish a more comprehensive security environment cooperating with an active data-centric (ADC) framework, we propose a cloud-based privacy-aware role-based access control (CPRBAC) service and an active auditing service (AAS). These components in the entire data protection framework contribute to the passive security mechanisms. They provide access control management and audit work based on a consistent security environment. We also discuss and implement full mobility management and data replica management related to the ADCu, which are regarded as significant factors to satisfy data accountability, availability, and scalability. We conduct a set of practical experiments and security evaluation on a mini-private cloud platform. The outcome of this research demonstrates the efficiency, feasibility, dependability, and scalability of protecting outsourced data in cloud by using the trust-oriented protection framework. To that end, we introduce an application applying the components and mechanisms of the trust-oriented security framework to protecting eHealth data in cloud. The novelty of this work lies in protecting cloud data in an ADCu that is not highly reliant on strong encryption schemes and third-party protection schemes. By proposing innovative structures, concepts, algorithms, and services, the major contribution of this thesis is that it helps cloud providers to deliver trust actively to cloud users, and encourages broader adoption of cloud-based solutions for data storage services in sensitive areas

Mutual query data sharing protocol for public key encryption through chosen-ciphertext attack in cloud environment

In this paper, we are proposing a mutual query data sharing protocol (MQDS) to overcome the encryption or decryption time limitations of exiting protocols like Boneh, rivest shamir adleman (RSA), Multi-bit transposed ring learning parity with noise (TRLPN), ring learning parity with noise (Ring-LPN) cryptosystem, key-Ordered decisional learning parity with noise (kO-DLPN), and KD_CS protocol’s. Titled scheme is to provide the security for the authenticated user data among the distributed physical users and devices. The proposed data sharing protocol is designed to resist the chosen-ciphertext attack (CCA) under the hardness solution for the query shared-strong diffie-hellman (SDH) problem. The evaluation of proposed work with the existing data sharing protocols in computational and communication overhead through their response time is evaluated