In this paper we define the overflow problem of a network coding storage system in which the encoding parameter and the storage parameter are mismatched. Through analyses and experiments, we first show the impacts of the overflow problem in a network coding scheme, which not only waste storage spaces, but also degrade coding efficiency. To avoid the overflow problem, we then develop the network coding based secure storage (NCSS) scheme. Thanks to considering both security and storage requirements in encoding procedures and distributed architectures, the NCSS can improve the performance of a cloud storage system from both the aspects of storage cost and coding processing time. We analyze the maximum allowable stored encoded data under the perfect secrecy criterion, and provide the design guidelines for the secure cloud storage system to enhance coding efficiency and achieve the minimal storage cost.
For secure storage over multiple clouds, similar to this work, the authors of @cite_26 proposed a security protection scheme to ensure that no symbols can be decoded by an eavesdropper, which is weaker than perfect secrecy. In @cite_4 , a link eavesdropping problem in a network-coded cloud storage system was investigated. A publicly verifiable protocol for network coded cloud storage was proposed in @cite_11 .
@cite_26 @cite_4 @cite_11
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This paper reveals an intrinsic relationship between secure cloud storage and secure network coding for the first time. Secure cloud storage was proposed only recently while secure network coding has been studied for more than ten years. Although the two areas are quite different in their nature and are studied independently, we show how to construct a secure cloud storage protocol given any secure network coding protocol. This gives rise to a systematic way to construct secure cloud storage protocols. Our construction is secure under a definition which captures the real world usage of the cloud storage. Furthermore, we propose two specific secure cloud storage protocols based on two recent secure network coding protocols. In particular, we obtain the first publicly verifiable secure cloud storage protocol in the standard model. We also enhance the proposed generic construction to support user anonymity and third-party public auditing, which both have received considerable attention recently. Finally, we prototype the newly proposed protocol and evaluate its performance. Experimental results validate the effectiveness of the protocol. We focus on the problem of secure distributed storage over multiple untrusted clouds or networks. Our main contribution is a low complexity scheme that relies on erasure coding techniques for achieving prescribed levels of confidentiality and reliability. Using matrices that have no singular square submatrices, we subject the original data to a linear transformation. The resulting coded symbols are then stored in different networks. This scheme allows users with access to a threshold number of networks to reconstruct perfectly the original data, while ensuring that eavesdroppers with access to any number of networks smaller than this threshold are unable to decode any of the original symbols. This holds even if the attackers are able to guess some of the missing symbols. We further quantify the achievable level of security, and analyze the complexity of the proposed scheme. Network coding is an important cloud storage technique, which can recover data with small repair bandwidth and high reliability compared to the existing erasure coding and replication methods. However, regardless of which data recovery technique is used, the repaired data in a geographically distributed cloud storage system are easy to be eavesdropped at the transmission link between the local datacenter and its remote backup site. This kind of network security issue is called link eavesdropping in this paper. For a network coded cloud storage system, we propose a systematic design methodology to determine the important data recovery system parameters for any specified security level. Through analysis, we present the performance curves to relate the remote repair bandwidth and the number of coded data fragments. Consequently, all the important system parameters of a network coded data recovery system, including the number of storage nodes and the link capacity between the datacenter and the backup site, can be precisely designed for satisfying different security level requirements. This paper aims to go beyond resilience into the study of security and local-repairability for distributed storage systems (DSSs). Security and local-repairability are both important as features of an efficient storage system, and this paper aims to understand the trade-offs between resilience, security, and local-repairability in these systems. In particular, this paper first investigates security in the presence of colluding eavesdroppers, where eavesdroppers are assumed to work together in decoding the stored information. Second, this paper focuses on coding schemes that enable optimal local repairs. It further brings these two concepts together to develop locally repairable coding schemes for DSS that are secure against eavesdroppers. The main results of this paper include: 1) an improved bound on the secrecy capacity for minimum storage regenerating codes; 2) secure coding schemes that achieve the bound for some special cases; 3) a new bound on minimum distance for locally repairable codes; 4) code construction for locally repairable codes that attain the minimum distance bound; and 5) repair-bandwidth-efficient locally repairable codes with and without security constraints. This paper addresses the issue of securing information stored on a distributed storage system from a passive eavesdropping attack. The security notion is perfect secrecy, i.e., the system is said to be secure only if the mutual information between the stored information and the observations at the adversary is zero. The paper summarizes state of the art on securing repair-efficient distributed storage systems. Then, storage systems that employ locally repairable codes with minimum bandwidth regenerating codes as local codes (MBR-LRCs) are investigated. A secure file size upper bound and a construction of secure MBR-LRCs are provided. These two are shown to match under special cases, establishing the secrecy capacity of these systems. To provide fault tolerance for cloud storage, recent studies propose to stripe data across multiple cloud vendors. However, if a cloud suffers from a permanent failure and loses all its data, then we need to repair the lost data from other surviving clouds to preserve data redundancy. We present a proxy-based system for multiple-cloud storage called NCCloud, which aims to achieve cost-effective repair for a permanent single-cloud failure. NCCloud is built on top of network-coding-based storage schemes called regenerating codes. Specifically, we propose an implementable design for the functional minimum-storage regenerating code (F-MSR), which maintains the same data redundancy level and same storage requirement as in traditional erasure codes (e.g., RAID-6), but uses less repair traffic. We implement a proof-of-concept prototype of NCCloud and deploy it atop local and commercial clouds. We validate the cost effectiveness of FMSR in storage repair over RAID-6, and show that both schemes have comparable response time performance in normal cloud storage operations. To provide fault tolerance for cloud storage, recent studies propose to stripe data across multiple cloud vendors. However, if a cloud suffers from a permanent failure and loses all its data, we need to repair the lost data with the help of the other surviving clouds to preserve data redundancy. We present a proxy-based storage system for fault-tolerant multiple-cloud storage called NCCloud, which achieves cost-effective repair for a permanent single-cloud failure. NCCloud is built on top of a network-coding-based storage scheme called the functional minimum-storage regenerating (FMSR) codes, which maintain the same fault tolerance and data redundancy as in traditional erasure codes (e.g., RAID-6), but use less repair traffic and, hence, incur less monetary cost due to data transfer. One key design feature of our FMSR codes is that we relax the encoding requirement of storage nodes during repair, while preserving the benefits of network coding in repair. We implement a proof-of-concept prototype of NCCloud and deploy it atop both local and commercial clouds. We validate that FMSR codes provide significant monetary cost savings in repair over RAID-6 codes, while having comparable response time performance in normal cloud storage operations such as upload download. With the increasing adoption of cloud computing for data storage, assuring data service reliability, in terms of data correctness and availability, has been outstanding. While redundancy can be added into the data for reliability, the problem becomes challenging in the “pay-as-you-use” cloud paradigm where we always want to efficiently resolve it for both corruption detection and data repair. Prior distributed storage systems based on erasure codes or network coding techniques have either high decoding computational cost for data users, or too much burden of data repair and being online for data owners. In this paper, we design a secure cloud storage service which addresses the reliability issue with near-optimal overall performance. By allowing a third party to perform the public integrity verification, data owners are significantly released from the onerous work of periodically checking data integrity. To completely free the data owner from the burden of being online after data outsourcing, this paper proposes an exact repair solution so that no metadata needs to be generated on the fly for repaired data. The performance analysis and experimental results show that our designed service has comparable storage and communication cost, but much less computational cost during data retrieval than erasure codes-based storage solutions. It introduces less storage cost, much faster data retrieval, and comparable communication cost comparing to network coding-based distributed storage systems. We consider the problem of secure distributed data storage under the paradigm of , in which no is leaked to the eavesdropper. More specifically, the eavesdropper cannot get any information about any individual message file or a small group of files. The key benefit of the weak security paradigm is that it incurs no loss in the storage capacity, which makes it practically appealing. In this paper, we present a coding scheme, using a coset coding based outer code and a Product-Matrix Minimum Bandwidth Regenerating code (proposed by ) as an inner code, that achieves weak security when the eavesdropper can observe any single storage node. We show that the proposed construction has good security properties and requires small finite field size. Regenerating codes are a class of codes for distributed storage networks that provide reliability and availability of data, and also perform efficient node repair. Another important aspect of a distributed storage network is its security. In this paper, we consider a threat model where an eavesdropper may gain access to the data stored in a subset of the storage nodes, and possibly also, to the data downloaded during repair of some nodes. We provide explicit constructions of regenerating codes that achieve information-theoretic secrecy capacity in this setting. Effortless data storage ''in the cloud'' is gaining popularity for personal, enterprise and institutional data backups and synchronisation as well as for highly scalable access from software applications running on attached compute servers. The data is usually access-protected, encrypted and replicated depending on the security and scalability needs. Despite the advances in technology, the practical usefulness and longevity of cloud storage is limited in today's systems, which severely impacts the acceptance and adoption rates. Therefore, we introduce a novel cloud storage management system which optimally combines storage resources from multiple providers so that redundancy, security and other non-functional properties can be adjusted adequately to the needs of the storage service consumer. The system covers the entire storage service lifecycle from the consumer perspective. Hence, a definition of optimality is first contributed which is bound to both the architecture and the lifecycle phases. Next, an ontology for cloud storage services is presented as a prerequisite for optimality. Furthermore, we present NubiSave, a user-friendly storage controller implementation with adaptable overhead which runs on and integrates into typical consumer environments as a central part of an overall storage system. Its optimality claims are validated in real-world scenarios with several commercial online and cloud storage providers. In recent years, due to the appealing features of cloud computing, large amount of data have been stored in the cloud. Although cloud based services offer many advantages, privacy and security of the sensitive data is a big concern. To mitigate the concerns, it is desirable to outsource sensitive data in encrypted form. Encrypted storage protects the data against illegal access, but it complicates some basic, yet important functionality such as the search on the data. To achieve search over encrypted data without compromising the privacy, considerable amount of searchable encryption schemes have been proposed in the literature. However, almost all of them handle exact query matching but not similarity matching, a crucial requirement for real world applications. Although some sophisticated secure multi-party computation based cryptographic techniques are available for similarity tests, they are computationally intensive and do not scale for large data sources. In this paper, we propose an efficient scheme for similarity search over encrypted data. To do so, we utilize a state-of-the-art algorithm for fast near neighbor search in high dimensional spaces called locality sensitive hashing. To ensure the confidentiality of the sensitive data, we provide a rigorous security definition and prove the security of the proposed scheme under the provided definition. In addition, we provide a real world application of the proposed scheme and verify the theoretical results with empirical observations on a real dataset. We address the problem of securing distributed storage systems against passive eavesdroppers that can observe a limited number of storage nodes. An important aspect of these systems is node failures over time, which demand a repair mechanism aimed at maintaining a targeted high level of system reliability. If an eavesdropper observes a node that is added to the system to replace a failed node, it will have access to all the data downloaded during repair, which can potentially compromise the entire information in the system.We are interested in determining the secrecy capacity of distributed storage systems under repair dynamics, i.e., the maximum amount of data that can be securely stored and made available to a legitimate user without revealing any information to any eavesdropper. We derive a general upper bound on the secrecy capacity and show that this bound is tight for the bandwidth-limited regime which is of importance in scenarios such as peer-to-peer distributed storage systems. We also provide a simple explicit code construction that achieves the capacity for this regime. Cloud computing is set of resources and services offered through the Internet. Cloud services are delivered from data centres located throughout the world. Cloud computing facilitates its consumers by providing virtual resources via internet. The rapid growth in field of "cloud computing" also increases severe security concerns. Security has remained a constant issue for Open Systems and internet, when we are talking about security, cloud really suffers. Lack of security is the only hurdle in wide adoption of cloud computing. Cloud computing is surrounded by many security issues like securing data and examining the utilization of cloud by the cloud computing vendors. This paper proposes a scheme to securely store and access of data via internet. We have used ECC based PKI for certificate procedure because the use of ECC significantly reduces the computation cost, message size and transmission overhead over RSA based PKI as 160-bit key size in ECC provides comparable security with 1024-bit key in RSA. We have designed Secured Cloud Storage Framework (SCSF). In this framework, users not only can securely store and access data in cloud but also can share data with multiple users through the unsecure internet in a secured way. This scheme can ensure the security and privacy of the data in the cloud. Data security in the cloud is a big concern that blocks the widespread use of the cloud for relational data management. First, to ensure data security, data confidentiality needs to be provided when data resides in storage as well as when data is dynamically accessed by queries. Prior works on query processing on encrypted data did not provide data confidentiality guarantees in both aspects. Tradeoff between secrecy and efficiency needs to be made when satisfying both aspects of data confidentiality while being suitable for practical use. Second, to support common relational data management functions, various types of queries such as exact queries, range queries, data updates, insertion and deletion should be supported. To address these issues, this paper proposes a comprehensive framework for secure and efficient query processing of relational data in the cloud. Our framework ensures data confidentiality using a salted IDA encoding scheme and column-access-via-proxy query processing primitives, and ensures query efficiency using matrix column accesses and a secure B+-tree index. In addition, our framework provides data availability and integrity. We establish the security of our proposal by a detailed security analysis and demonstrate the query efficiency of our proposal through an experimental evaluation. In a document network such as a citation network of scientific documents, web-logs, etc., the content produced by authors exhibits their interest in certain topics. In addition some authors influence other authors' interests. In this work, we propose to model the influence of cited authors along with the interests of citing authors. Moreover, we hypothesize that apart from the citations present in documents, the context surrounding the citation mention provides extra topical information about the cited authors. However, associating terms in the context to the cited authors remains an open problem. We propose novel document generation schemes that incorporate the context while simultaneously modeling the interests of citing authors and influence of the cited authors. Our experiments show significant improvements over baseline models for various evaluation criteria such as link prediction between document and cited author, and quantitatively explaining unseen text. Working in various service models ranging from SaaS, PaaS, to IaaS, cloud computing is viewed by many as anew revolution in IT, and could reshape the paradigm of how IT industry works today. Storage services are a fundamental function offered by cloud computing. A typical use scenario of the cloud storage services is that an enterprise outsources its database to the cloud and authorizes multiple users to access the database. In such cases of database outsourcing, data encryption is a good approach enabling the data owner to retain its control over the outsourced data. Searchable encryption is a cryptographic primitive allowing for private keyword based search over the encrypted database. The above setting of enterprise outsourcing database to the cloud requires multi-user searchable encryption, whereas virtually all existing schemes consider the single-user setting. To bridge this gap, we are motivated to propose a practical multi-user searchable encryption scheme, which has a number of advantages over the known approaches. The associated model and security requirements are also formulated. Multi-tenancy is used for efficient resource utilization when cloud resources are shared across multiple customers. In cloud applications, the data layer is often the prime candidate for multi-tenancy, and usually comprises a combination of different cloud storage solutions such as relational and non-relational databases, and blob storage. Each of these storage types is different, requiring its own partitioning schemes to ensure tenant isolation and scalability. Current multi-tenant data architectures are implemented mainly through manual coding techniques that tend to be time consuming and error prone. As an alternative, we propose a domain-specific modeling language, CadaML, that provides concepts and notations to model a multi-tenant data architecture in an abstract way. CadaML also provides tools to validate the data architecture and automatically produce application code to implement said architecture. As the rapid growth of data, many storage systems have used erasure codes instead of replication to reduce the storage cost under the same level of reliability. Maximum-Distance- Separable (MDS) codes have been the most widely adopted, due to their optimal storage efficiency. It is well understood that the application of codes in storage systems, where the data is less frequently accessed. For the data, which is stored in cloud storage systems, is frequently accessed (or so-called “hot data”), the performance of data-retrieving is the key metric. To the best of our knowledge, there has been only a little work on the performance of data-retrieving in cloud storage systems with erasure codes. They combined queuing theory with coding theory to analyze and optimize the effect of MDS codes in the performance of data-retrieving. Their studies were based on MDS codes and they gave the solutions. In this paper, we transfer the perspective of study of based on MDS codes to that of optimizing MDS codes in order to improve the performance of data-retrieving, that is, from optimizing the system retrieving strategies to optimizing the coding schemes. We apply Network Coding to optimize the coding schemes and propose a new family of MDS codes, which reach optimal performance of dataretrieving in theory. As organizations become increasingly reliant on cloud computing for servicing their data storage requirements, the need to govern access control at finer granularities becomes particularly important. This challenge is increased by the lack of policy supporting data migration across geographic boundaries and through organizations with divergent regulatory policies. In this paper, we present an architecture for secure and distributed management of provenance, enabling its use in security-critical applications. Provenance, a metadata history detailing the derivation of an object, contains information that allows for expressive, policy-independent access control decisions. We consider how to manage and validate the metadata of a provenance-aware cloud system, and introduce protocols that allow for secure transfer of provenance metadata between end hosts and cloud authorities. Using these protocols, we develop a provenance-based access control mechanism for Cumulus cloud storage, capable of processing thousands of operations per second on a single deployment. Through the introduction of replicated components, we achieve overhead costs of just 14 , demonstrating that provenance-based access control is a practical and scalable solution for the cloud.