Cloud Storage Scheme Research Articles

Chronos+: An Accurate Blockchain-based Time-stamping Scheme for Cloud Storage

We propose Chronos $^{{\mathbf +}}$ + , an accurate blockchain-based time-stamping scheme for outsourced data, where both the storage and time-stamping services are provided by cloud service providers. Specifically, Chronos $^{{\mathbf +}}$ + integrates a file into a transaction on a blockchain once the file is created, which guarantees the file's latest creation time to be the time when the block containing the transaction is appended to the blockchain. A sufficient number of consecutive blocks that are latest confirmed on the blockchain is embedded into the file at the creation time. These blocks serve as a time-dependent random seed to prove the earliest creation time, due to blockchains’ chain quality property. Chronos $^{{\mathbf +}}$ + makes the file's timestamp corresponding to a time interval formed by the earliest and latest creation times which are derived from the heights of the corresponding blocks. Due to blockchains’ chain growth property, such a height-derived timestamp can ensure that the time intervals’ range is within a few minutes so as to guarantee the accuracy. We also point out potential threats towards outsourced time-sensitive files and present security analyses to prove that Chronos $^{{\mathbf +}}$ + is secure against these threats. Comprehensive performance evaluations demonstrate the efficiency and practicality of Chronos $^{{\mathbf +}}$ + .

An efficient $$\mathcal{iO}$$ i O -based data integrity verification scheme for cloud storage

An efficient $$\mathcal{iO}$$ i O -based data integrity verification scheme for cloud storage

An Efficient and Secure Cloud Storage Scheme with Hidden Access Patterns

An Efficient and Secure Cloud Storage Scheme with Hidden Access Patterns

AC-RRNS: Anti-collusion secured data sharing scheme for cloud storage

Cloud security issues are important factors for data storage and processing. Apart from the existing security and reliability problems of traditional distributed computing, there are new security and reliability problems. They include attacks on a virtual machine, attacks on the synchronization keys, and so on. According to the assessment of international experts in the field of cloud security, there are risks of cloud collusion under uncertain conditions. To mitigate this type of uncertainty and reduce harms it can cause, we propose AC-RRNS algorithm based on modified threshold Asmuth–Bloom and Mignotte secret sharing schemes. We prove that the algorithm satisfies the formal definition of computational security. If the adversary coalition knows the secret shares, but does not know the secret key, the probability to obtain the secret is less than 1/(2l⋅(k−1)(2l−k−1)). The probability is less than 1/2(l−1) with unknown secret shares and known secret key, and 1/2l⋅k with unknown secret key. Its complexity is equal to brute-force method. We demonstrate that the proposed scheme ensures security under several types of attacks. We propose approaches for selection of parameters for AC-RRNS secret sharing scheme to optimize the system behavior and data redundancy of encryption.

Block-secure: Blockchain based scheme for secure P2P cloud storage

With the development of Internet technology, the volume of data is increasing tremendously. To tackle with large-scale data, more and more applications choose to enlarge the storage capacity of users’ terminals with the help of cloud platforms. Before storing data to an untrusted cloud server, some measures should be adopted to guarantee the data security. However, the communication overhead will increase dramatically when users transmit files encrypted by a traditional encryption scheme. In this paper, we address the above problems by proposing a blockchain-based security architecture for distributed cloud storage, where users can divide their own files into encrypted data chunks, and upload those data chunks randomly into the P2P network nodes that provide free storage capacity. We customize a genetic algorithm to solve the file block replica placement problem between multiple users and multiple data centers in the distributed cloud storage environment. Numerical results show that the proposed architecture outperforms the traditional cloud storage architectures in terms of file security and network transmission delay. On average, the file loss rate based on the simulation assumptions utilized in this paper is close to 0% on our architecture while it’s nearly 100% and 71.66% on the architecture with single data center and the distributed architecture using genetic algorithm. Besides, with proposed scheme, the transmission delay on the proposed architecture is reduced by 39.28% and 76.47% on average on the user’s number and the number of file block replicas, respectively, in comparison to the architecture with single data center. Meanwhile, the transmission delay of file block replicas is also reduced by 41.36% on average than that on the distributed architecture using genetic algorithm.

Enhanced Secure Thresholded Data Deduplication Scheme for Cloud Storage

As more corporate and private users outsource their data to cloud storage, recent data breach incidents make end-to-end encryption increasingly desirable. Unfortunately, semantically secure encryption renders various cost-effective storage optimization techniques, such as data deduplication, ineffective. On this ground Stanek et al. [1] introduced the concept of “data popularity” arguing that data known/owned by many users do not require as strong protection as unpopular data; based on this, Stanek et al. presented an encryption scheme, where the initially semantically secure ciphertext of a file is transparently downgraded to a convergent ciphertext that allows for deduplication as soon as the file becomes popular. In this paper we propose an enhanced version of the original scheme. Focusing on practicality, we modify the original scheme to improve its efficiency and emphasize clear functionality. We analyze the efficiency based on popularity properties of real datasets and provide a detailed performance evaluation, including comparison to alternative schemes in real-like settings. Importantly, the new scheme moves the handling of sensitive decryption shares and popularity state information out of the cloud storage, allowing for improved security notion, simpler security proofs and easier adoption. We show that the new scheme is secure under the Symmetric External Diffie-Hellman assumption in the random oracle model.

Efficient Multi-user Similarity Search Over Encrypted Data in Cloud Storage

In cloud-assisted data outsourcing systems, the privacy of sensitive data is a major concern. Thus, data are uploaded in encrypted form in many cloud applications while providing some basic yet critical functionalities, such as the ability to search. Similarity search over encrypted data provides decryptionless similarity testing between data and search queries which are encrypted by the data owner and users, respectively. However, previous similarity search schemes supporting multi-user settings incur unreasonable communication costs between the users and data owners during the search. In this paper, we propose efficient multi-user similarity search schemes for cloud storage. Specifically, the proposed schemes enable flexible similarity searches over encrypted data even when the given data have different format, encoding, or editing. The proposed similarity search schemes can guarantee asymptotically optimal performance for multi-user settings. We rigorously prove the proposed schemes are adaptively semantic secure. We also conduct an experimental analysis to demonstrate the applicability of the proposed scheme in practical cloud systems.

Multiuser access control searchable privacy‐preserving scheme in cloud storage

SummarySearchable encryption scheme‐based ciphertext‐policy attribute‐based encryption (CP‐ABE) is a effective scheme for providing multiuser to search over the encrypted data on cloud storage environment. However, most of the existing search schemes lack the privacy protection of the data owner and have higher computation time cost. In this paper, we propose a multiuser access control searchable privacy‐preserving scheme in cloud storage. First, the data owner only encrypts the data file and sets the access control list of multiuser and multiattribute for search data file. And the computing operation, which generates the attribute keys of the users' access control and the keyword index, is given trusted third party to perform for reducing the computation time of the data owner. Second, using CP‐ABE scheme, trusted third party embeds the users' access control attributes into their attribute keys. Only when those embedded attributes satisfy the access control list, the ciphertext can be decrypted accordingly. Finally, when the user searches data file, the keyword trap door is no longer generated by the user, and it is handed to the proxy server to finish. Also, the ciphertext is predecrypted by the proxy sever before the user performs decryption. In this way, the flaw of the client's limited computation resource can be solved. Security analysis results show that this scheme has the data privacy, the privacy of the search process, and the collusion‐resistance attack, and experimental results demonstrate that the proposed scheme can effectively reduce the computation time of the data owner and the users.

An Optimization Approach Towards a Proof of Retrievability Scheme for Cloud Storage

An Optimization Approach Towards a Proof of Retrievability Scheme for Cloud Storage

An ORAM-based privacy preserving data sharing scheme for cloud storage

Data sharing is one of the basic applications for cloud storage, which is inherently suitable for scalability and multitenancy feature of cloud computing. Generally, for security and privacy concerns, clients tend to conceal (e.g. encrypt) their data content. However, access patterns, usually generated by behavior of users in sharing data rather than data content itself, may cause severe sensitive information leakage . Recently, oblivious random access memory (ORAM) has drawn increasingly attention as it is an ideal cryptographic tool for access pattern hiding. However, the existing ORAM-based data sharing schemes involve various deficiencies, either in high complexity for computation or heavy reliance of complex cryptography primitives. Inspired by the former schemes, in this paper we propose a novel ORAM based data sharing scheme with high security guarantee and high efficiency. The scheme can prevent the data block from arbitrary modification through Shuffle Correctness Proof. The security of the scheme is based on the IND-CPA security of encryption scheme, the unforgeability of Identity-Based signature and the security properties of basic Path-ORAM. Analysis shows that the scheme has the optimal computation and communication complexity.

Decentralized attribute-based encryption and data sharing scheme in cloud storage

In this paper, we consider the problems of data sharing between multiple distrusted authorities. Prior solutions rely on trusted third parties such as CAs, or are susceptible to collusion between malicious authorities, which can comprise the security of honest ones. In this paper, we propose a new multi-authority data sharing scheme — Decentralized Multi-Authority ABE (DMA), which is derived from CP-ABE that is resilient to these types of misbehavior. Our system distinguishes between a data owner (DO) principal and attribute authorities (AAs): the DO owns the data but allows AAs to arbitrate access by providing attribute labels to users. The data is protected by policy encryption over these attributes. Unlike prior systems, attributes generated by AAs are not user-specific, and neither is the system susceptible to collusion between users who try to escalate their access by sharing keys. We prove our scheme correct under the Decisional Bilinear Diffie-Hellman (DBDH) assumption; we also include a complete end-to-end implementation that demonstrates the practical efficacy of our technique.

A Three-Layer Privacy Preserving Cloud Storage Scheme Based on Computational Intelligence in Fog Computing

Recent years witness the development of cloud computing technology. With the explosive growth of unstructured data, cloud storage technology gets more attention and better development. However, in current storage schema, user's data is totally stored in cloud servers. In other words, users lose their right of control on data and face privacy leakage risk. Traditional privacy protection schemes are usually based on encryption technology, but these kinds of methods cannot effectively resist attack from the inside of cloud server. In order to solve this problem, we propose a three-layer storage framework based on fog computing. The proposed framework can both take full advantage of cloud storage and protect the privacy of data. Besides, Hash-Solomon code algorithm is designed to divide data into different parts. Then, we can put a small part of data in local machine and fog server in order to protect the privacy. Moreover, based on computational intelligence, this algorithm can compute the distribution proportion stored in cloud, fog, and local machine, respectively. Through the theoretical safety analysis and experimental evaluation, the feasibility of our scheme has been validated, which is really a powerful supplement to existing cloud storage scheme.

Fog-based storage technology to fight with cyber threat

The recent emergence of cloud computing has drastically influenced everyone’s perception of infrastructure architectures, data transmission and other aspects. With the advent of both mobile networks and cloud computing, the computationally-intensive services are moving to the cloud, and the end user’s mobile device is used as an interface to access these services. However, cyber threats are also becoming various and sophisticated, which will endanger the security of users’ private data. In traditional service mode, users’ data is totally stored in the cloud, they lose the right of control on their data and face cyber threats such as data loss and malicious modification. To this end, we propose a novel cloud storage scheme based on fog computing. In our scheme, user’s private data is separately stored in the cloud and fog servers. By this way, the integrity, availability and confidentiality of user’s data can be ensured because the data is retrieved from cloud as well as fog, which is safer. We implement a system prototype and design a series of mechanisms. Extensive experiments results also validate the proposed scheme and methods.

An Improved Key Management Scheme in Cloud Storage

Nowadays, cloud services are used by numerous people all around the globe. One of its major applications is in the field of cloud storage. Users can store data in cloud without the need to have har...

Cloud Storage for Electronic Health Records Based on Secret Sharing With Verifiable Reconstruction Outsourcing

Deploying electronic health records (EHRs) is now an undisputable trend in healthcare systems. Through affording benefits like flexibility and low cost, the cutting-cloud cloud storage is becoming a popular solution to store a massive amount of EHRs to depress the local storage. Nevertheless, storing sensitive information such as health records on the cloud incurs severe security and privacy risks. In this paper, we propose a novel cloud storage system for EHRs which fully ensures the data privacy by employing the Shamir’s secret sharing. In this system, an EHR is divided into multiple segments by a healthcare center, and the segments are distributed to numerous cloud servers. When retrieving the EHR, the healthcare center captures segments from partial cloud servers and reconstructs the EHRs. Meanwhile, in reality, the reconstruction of a shared EHR could be much burdensome for a healthcare center or a patient, we thus propose a practical cloud storage scheme which outsources the reconstruction of a shared EHR to a cloud computing service provider. Such a solution can drastically boost the efficiency of the proposed scheme. As far as we know, our scheme is the first to define reconstruction outsourcing concept in all cloud storage schemes for EHRs based on secret sharing, and the results of outsourcing reconstruction can be verified by healthcare centers or patients in our scheme. The theoretical analysis and experimental results also support that our proposed scheme is secure and efficient.

A Network Coding Based Cloud Storage Scheme

With this paper, we propose a network coding based cloud storage scheme. The storage system is in the form of an m * n data array. The n columns stand for n storage nodes, which are comprised of a part of systematic nodes storing source symbols and a part of nonsystematic nodes storing parity symbols. Every row of the data array is a (n, k) systematic Maximum Distance Separable (MDS) code. A source symbol is only involved in the encoding with the unique row; it locates at and is not used by other rows. Such a design significantly decreases the complexity of encoding and decoding. Moreover, in case of single node failures, we use interference alignment to further reduce repair bandwidth. Compared to some existing cloud storage schemes, our scheme significantly reduces resource consumption on storage, update bandwidth and repair bandwidth.

Efficiently Revocable and Searchable Attribute-Based Encryption Scheme for Mobile Cloud Storage

Attribute-based encryption (ABE) is suitable for mobile cloud storage to protect data confidentiality and realize fine-grained data access control. It is essential for ABE schemes to achieve attribute revocation as users’ attributes may be changed frequently. Keyword search over encrypted data also needs to be solved in the mobile cloud storage. In addition, computational efficiency is a consideration for the resource-constrained mobile device. Focusing on the above-mentioned problems, an efficiently revocable and searchable ABE (RSABE) scheme for the mobile cloud storage is proposed. In our scheme, the function of attribute revocation is efficiently achieved by delegating the update of secret key and ciphertext to the powerful cloud server. Keyword search is also supported, in which data owners and users can generate the keywords index and search trapdoor, respectively, without relying on always online trusted authority. Furthermore, an outsourced decryption technology is used to reduce the computational load of decryption on user side. Our RSABE scheme is proven to be semantically secure against selective ciphertext policy and chosen plaintext attack, and to be secure against chosen keyword attack in the random oracle model. Finally, performance evaluation demonstrates that our scheme is highly efficient.

Lattice-based searchable public-key encryption scheme for secure cloud storage

Lattice-based searchable public-key encryption scheme for secure cloud storage

Region-Based Prediction for Image Compression in the Cloud.

Thanks to the increasing number of images stored in the cloud, external image similarities can be leveraged to efficiently compress images by exploiting inter-images correlations. In this paper, we propose a novel image prediction scheme for cloud storage. Unlike current state-of-the-art methods, we use a semi-local approach to exploit inter-image correlation. The reference image is first segmented into multiple planar regions determined from matched local features and super-pixels. The geometric and photometric disparities between the matched regions of the reference image and the current image are then compensated. Finally, multiple references are generated from the estimated compensation models and organized in a pseudo-sequence to differentially encode the input image using classical video coding tools. Experimental results demonstrate that the proposed approach yields significant rate-distortion performance improvements compared with the current image inter-coding solutions such as high efficiency video coding.

Blockchain-based publicly verifiable data deletion scheme for cloud storage

With the rapid development of cloud storage, more and more data owners store their data on the remote cloud, that can reduce data owners’ overhead because the cloud server maintaining the data for them, e.g., storing, updating and deletion. However, that leads to data deletion becomes a security challenge because the cloud server may not delete the data honestly for financial incentives. Recently, plenty of research works have been done on secure data deletion. However, most of the existing methods can be summarized with the same protocol essentially, which called “one-bit-return” protocol: the storage server deletes the data and returns a one-bit result. The data owner has to believe the returned result because he cannot verify it. In this paper, we propose a novel blockchain-based data deletion scheme, which can make the deletion operation more transparent. In our scheme, the data owner can verify the deletion result no matter how malevolently the cloud server behaves. Besides, with the application of blockchain, the proposed scheme can achieve public verification without any trusted third party.