Blockchain & Multi-Agent System: A New Promising Approach for Cloud Data Integrity Auditing with Deduplication

Recently, data storage represents one of the most important services in Cloud Computing. The cloud provider should ensure two major requirements which are data integrity and storage efficiency. Blockchain data structure and the efficient data deduplication represent possible solutions to address these exigencies. Several approaches have been proposed, some of them implement deduplication in Cloud server side, which involves a lot of computation to eliminate the redundant data and it becomes more and more complex. Therefore, this paper proposed an efficient, reliable and secure approach, in which the authors propose a Multi-Agent System in order to manipulate deduplication technique that permits to reduce data volumes thereby reduce storage overhead. On the other side, the loss of physical control over data introduces security challenges such as data loss, data tampering and data modification. To solve similar problems, the authors also propose Blockchain as a database for storing metadata of client files. This database serves as logging database that ensures data integrity auditing function

SoK: A Practical Cost Comparison Among Provable Data Possession Schemes

Provable Data Possession (PDP) schemes provide users with the ability to efficiently audit and verify the integrity of data stored with potentially unreliable third-parties, such as cloud storage service providers. While dozens of PDP schemes have been developed, no PDP schemes have been practically implemented with an existing cloud service. This work attempts to provide a starting point for the integration of PDP schemes with cloud storage service providers by providing a cost analysis of PDP schemes. This cost analysis is performed by implementing and analyzing five PDP schemes representative of the dozens of various PDP approaches. This paper provides analysis of the overhead and performance of each of these schemes to generate a comparable cost for each scheme using real-world cloud pricing models. Results show that the total cost of each scheme is comparable for smaller file sizes, but for larger files this cost can vary across schemes by an order of magnitude. Ultimately, the difference in cost between the simple MAC-based PDP scheme and the most efficient PDP scheme is negligible. While the MAC-PDP scheme may not be the most efficient, no other scheme improving upon it\u27s complexity can be implemented without the use of additional services or APIs leading to the conclusion that the simplest, storage only PDP scheme is the most practical to implement. Furthermore, the findings in this paper suggest that, in general, PDP schemes optimize on an inaccurate cost model and that future schemes should consider the existing economic realities of cloud services

Efficient Method Based on Blockchain Ensuring Data Integrity Auditing with Deduplication in Cloud

With the rapid development of cloud storage, more and more cloud clients can store and access their data anytime, from anywhere and using any device. Data deduplication may be considered an excellent choice to ensure data storage efficiency. Although cloud technology offers many advantages for storage service, it also introduces security challenges, especially with regards to data integrity, which is one of the most critical elements in any system. A data owner should thus enable data integrity auditing mechanisms. Much research has recently been undertaken to deal with these issues. In this paper, we propose a novel blockchain-based method, which can preserve cloud data integrity checking with data deduplication. In our method, a mediator performs data deduplication on the client side, which permits a reduction in the amount of outsourced data and a decrease in the computation time and the bandwidth used between the enterprise and the cloud service provider. This method supports private and public auditability. Our method also ensures the confidentiality of a client's data against auditors during the auditing process

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

Efficient Dynamic Provable Possession of Remote Data via Update Trees

The emergence and wide availability of remote storage service providers prompted work in the security community that allows a client to verify integrity and availability of the data that she outsourced to an untrusted remove storage server at a relatively low cost. Most recent solutions to this problem allow the client to read and update (i.e., insert, modify, or delete) stored data blocks while trying to lower the overhead associated with verifying the integrity of the stored data. In this work we develop a novel scheme, performance of which favorably compares with the existing solutions. Our solution enjoys a number of new features such as a natural support for operations on ranges of blocks, revision control, and support for multiple user access to shared content. The performance guarantees that we achieve stem from a novel data structure termed a balanced update tree and removing the need to verify update operations

New directions for remote data integrity checking of cloud storage

Cloud storage services allow data owners to outsource their data, and thus reduce their workload and cost in data storage and management. However, most data owners today are still reluctant to outsource their data to the cloud storage providers (CSP), simply because they do not trust the CSPs, and have no confidence that the CSPs will secure their valuable data. This dissertation focuses on Remote Data Checking (RDC), a collection of protocols which can allow a client (data owner) to check the integrity of data outsourced at an untrusted server, and thus to audit whether the server fulfills its contractual obligations. Robustness has not been considered for the dynamic RDCs in the literature. The R-DPDP scheme being designed is the first RDC scheme that provides robustness and, at the same time, supports dynamic data updates, while requiring small, constant, client storage. The main challenge that has to be overcome is to reduce the client-server communication during updates under an adversarial setting. A security analysis for R-DPDP is provided. Single-server RDCs are useful to detect server misbehavior, but do not have provisions to recover damaged data. Thus in practice, they should be extended to a distributed setting, in which the data is stored redundantly at multiple servers. The client can use RDC to check each server and, upon having detected a corrupted server, it can repair this server by retrieving data from healthy servers, so that the reliability level can be maintained. Previously, RDC has been investigated for replication-based and erasure coding-based distributed storage systems. However, RDC has not been investigated for network coding-based distributed storage systems that rely on untrusted servers. RDC-NC is the first RDC scheme for network coding-based distributed storage systems to ensure data remain intact when faced with data corruption, replay, and pollution attacks. Experimental evaluation shows that RDC-NC is inexpensive for both the clients and the servers. The setting considered so far outsources the storage of the data, but the data owner is still heavily involved in the data management process (especially during the repair of damaged data). A new paradigm is proposed, in which the data owner fully outsources both the data storage and the management of the data. In traditional distributed RDC schemes, the repair phase imposes a significant burden on the client, who needs to expend a significant amount of computation and communication, thus, it is very difficult to keep the client lightweight. A new self-repairing concept is developed, in which the servers are responsible to repair the corruption, while the client acts as a lightweight coordinator during repair. To realize this new concept, two novel RDC schemes, RDC-SR and ERDC-SR, are designed for replication-based distributed storage systems, which enable Server-side Repair and minimize the load on the client side. Version control systems (VCS) provide the ability to track and control changes made to the data over time. The changes are usually stored in a VCS repository which, due to its massive size, is often hosted at an untrusted CSP. RDC can be used to address concerns about the untrusted nature of the VCS server by allowing a data owner to periodically check that the server continues to store the data. The RDC-AVCS scheme being designed relies on RDC to ensure all the data versions are retrievable from the untrusted server over time. The RDC-AVCS prototype built on top of Apache SVN only incurs a modest decrease in performance compared to a regular (non-secure) SVN system

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

Replication, Security, and Integrity of Outsourced Data in Cloud Computing Systems

In the current era of digital world, the amount of sensitive data produced by many organizations is outpacing their storage ability. The management of such huge amount of data is quite expensive due to the requirements of high storage capacity and qualified personnel. Storage-as-a-Service (SaaS) offered by cloud service providers (CSPs) is a paid facility that enables organizations to outsource their data to be stored on remote servers. Thus, SaaS reduces the maintenance cost and mitigates the burden of large local data storage at the organization's end. For an increased level of scalability, availability and durability, some customers may want their data to be replicated on multiple servers across multiple data centers. The more copies the CSP is asked to store, the more fees the customers are charged. Therefore, customers need to have a strong guarantee that the CSP is storing all data copies that are agreed upon in the service contract, and these copies remain intact. In this thesis we address the problem of creating multiple copies of a data file and verifying those copies stored on untrusted cloud servers. We propose a pairing-based provable multi-copy data possession (PB-PMDP) scheme, which provides an evidence that all outsourced copies are actually stored and remain intact. Moreover, it allows authorized users (i.e., those who have the right to access the owner's file) to seamlessly access the file copies stored by the CSP, and supports public verifiability. We then direct our study to the dynamic behavior of outsourced data, where the data owner is capable of not only archiving and accessing the data copies stored by the CSP, but also updating and scaling (using block operations: modification, insertion, deletion, and append) these copies on the remote servers. We propose a new map-based provable multi-copy dynamic data possession (MB-PMDDP) scheme that verifies the intactness and consistency of outsourced dynamic multiple data copies. To the best of our knowledge, the proposed scheme is the first to verify the integrity of multiple copies of dynamic data over untrusted cloud servers. As a complementary line of research, we consider protecting the CSP from a dishonest owner, who attempts to get illegal compensations by falsely claiming data corruption over cloud servers. We propose a new cloud-based storage scheme that allows the data owner to benefit from the facilities offered by the CSP and enables mutual trust between them. In addition, the proposed scheme ensures that authorized users receive the latest version of the outsourced data, and enables the owner to grant or revoke access to the data stored by cloud servers

Cost comparison among provable data possession schemes

Provable data possession (PDP) provides mechanisms to eciently audit the integrity of data held by third parties, like cloud service providers. While multiple PDP schemes have been proposed, there is no research to date that provides in-depth cost analysis for PDP. This research fills that gap by (1) collecting and analyzing cost data for four PDP schemes, (2) providing generic cost models (math-ematical formulae expressing abstract models which can be used to infer future cost), and (3) comparing overall cost eciency of each PDP scheme. For the schemes considered in this study, we find all have nearly identical costs in practice; however, sophisticated schemes designed with low communication complexity have higher preprocessing or storage costs which, depending on audit param-eters, impact total scheme cost. We conclude that MAC-PDP and CPOR schemes are similar, whereas the cost of A-PDP becomes relatively expensive at large file sizes. Our basis cost projections show tagging, storing and auditing a file for one year at one audit per hour is at least $160 for a 1 GB file,$170 for a 1 TB file, and $2,000 for a 1 PB file using a cost model based on the Amazon S3 service.http://archive.org/details/costcomparisonmo1094548485Outstanding ThesisLieutenant, United States NavyApproved for public release; distribution is unlimited