Remote Data Integrity Checking Scheme Research Articles

Certificateless Reliable and Privacy-Preserving Auditing of Group Shared Data for FOG-CPSs

FOG-enabled cyber-physical systems (FOG-CPSs) open new security challenges as the local edge devices are easier to compromise than a traditional cloud server. Remote data integrity checking (RDIC) plays an important role in safeguarding against data corruption from a storage server. Certificateless cryptography (CLPKC)-based RDIC schemes do not suffer from the drawbacks of the public key infrastructure (PKI)-based RDIC protocols. Most of the CLPKC-based RDIC schemes proposed in the literature deal with personal data. However, in a FOG-CPS, it is also important to audit a data file shared by a group of edge devices. Most of the existing group shared data auditing schemes lack mechanisms to defend against a semi-trusted data auditor applicable for a FOG-CPS scenario. In order to address these issues, in this paper, we propose a novel CLPKC-based group shared data auditing protocol tailored to the specific security requirements of a FOG-CPS. Besides, we perform a detailed cryptanalysis of two existing CLPKC-based privacy-preserving group shared data auditing schemes. The formal security analysis of our proposed protocol establishes metadata and data integrity proof unforgeability and claimed zero-knowledge privacy and reliability properties through rigorous proofs in the random oracle model setting. Performance evaluations establish the efficiency of our proposed protocol.

Security Analysis and Improvements on a Remote Integrity Checking Scheme for Regenerating-Coding-Based Distributed Storage

Enabling remote data integrity checking with failure recovery becomes exceedingly critical in distributed cloud systems. With the properties of a lower repair bandwidth while preserving fault tolerance, regenerating coding and network coding (NC) have received much attention in the coding-based storage field. Recently, an outstanding outsourced auditing scheme named NC-Audit was proposed for regenerating-coding-based distributed storage. The scheme claimed that it can effectively achieve lightweight privacy-preserving data verification remotely for these networked distributed systems. However, our algebraic analysis shows that NC-Audit can be easily broken due to a potential defect existing in its schematic design. That is, an adversarial cloud server can forge some illegal blocks to cheat the auditor with a high probability when the coding field is large. From the perspective of algebraic security, we propose a remote data integrity checking scheme RNC-Audit by resorting to hiding partial critical information to the server without compromising system performance. Our evaluation shows that the proposed scheme has significantly lower overhead compared to the state-of-the-art schemes for distributed remote data auditing.

RDIC: A blockchain-based remote data integrity checking scheme for IoT in 5G networks

Internet of things (IoT) is one of the main application scenarios of 5th generation mobile networks (5G). Along with the rapid development of 5G, IoT terminal devices will create big data. Generally, IoT terminal devices are lightweight user equipments, for example, wearable devices. In order to take use of these lightweight terminal devices, it is a feasible way to outsource these created big data to the public cloud. When these data are out of the client’s control, it is of crucial importance to ensure the remote data integrity. To solve the weaknesses of the existing remote data integrity checking schemes, we propose the concept of blockchain-based remote data integrity checking (RDIC) scheme for big data. The new concept makes use of blockchain technique which greatly improves the efficiency and security of RDIC. First, the system model and security definition are given for the proposed RDIC scheme by using blockchain. Then, by using efficient modular arithmetic, RSA digital signature, blockchain, etc, we construct a lightweight blockchain-based RDIC scheme. Finally, we analyze its security and performance. The detailed analysis shows that our scheme is provably secure and lightweight.

Blockchain-based privacy-preserving remote data integrity checking scheme for IoT information systems

Remote data integrity checking is of great importance to the security of cloud-based information systems. Previous works generally assume a trusted third party to oversee the integrity of the outsourced data, which may be invalid in practice. In this paper, we utilize the blockchain to construct a novel privacy-preserving remote data integrity checking scheme for Internet of Things (IoT) information management systems without involving trusted third parties. Our scheme leverages the Lifted EC-ElGamal cryptosystem, bilinear pairing, and blockchain to support efficient public batch signature verifications and protect the security and data privacy of the IoT systems. The results of the experiment demonstrate the efficiency of our scheme.

Privacy-enhanced remote data integrity checking with updatable timestamp

Remote data integrity checking (RDIC) enables clients to verify whether the outsourced data is intact without keeping a copy locally or downloading it. Nevertheless, the existing RDIC schemes do not support the pay-as-you-go (PAYG) payment model, where the payment is decided by the volume and duration of the outsourced data. Specifically, none of the existing works have considered the client’s control over changes in storage duration. In this paper, we propose an RDIC scheme to simultaneously check the data content and storage duration represented by an updatable timestamp via the third-party auditor (TPA). Also, our proposed scheme achieves indistinguishable privacy (IND-privacy) against TPA for both data content and timestamp. To bind the content and timestamp in the authenticator and support efficient timestamp update, we construct the authenticator with the randomizable structure-preserving signature (SPS). Additionally, we utilize the Groth-Sahai proof and range proof to provide the IND-privacy and guarantee the timestamp validation in the auditing phase. We formalize the definition and security model and provide the formal proof of our scheme. We also present the theoretical and experimental performance analysis to demonstrate that our scheme is comparable to the previous RDIC schemes which do not consider the storage time.

Identity-Based Privacy Preserving Remote Data Integrity Checking for Cloud Storage

Although cloud storage service enables people easily maintain and manage amounts of data with lower cost, it cannot ensure the integrity of people's data. In order to audit the correctness of the data without downloading them, many remote data integrity checking (RDIC) schemes have been presented. Most existing schemes ignore the important issue of data privacy preserving and suffer from complicated certificate management derived from public key infrastructure. To overcome these shortcomings, this article proposes a new Identity-based RDIC scheme that makes use of homomorphic verifiable tag to decrease the system complexity. The original data in proof are masked by random integer addition, which protects the verifier from obtaining any knowledge about the data during the integrity checking process. Our scheme is proved secure under the assumption of computational Diffie–Hellman problem. Experiment result exhibits that our scheme is very efficient and feasible for real-life applications.

Efficient, dynamic and identity-based Remote Data Integrity Checking for multiple replicas

Nowadays, cloud storage plays an increasingly important role in our daily life. However, the cloud users do not have the physical possession of their own data anymore. To confirm whether the outsourced files are maintained intact without downloading them entirely, a mechanism namely Remote Data Integrity Checking (RDIC) is invented. Currently, some RDIC schemes allow the data owners with limited computation or communication power to delegate the checking task to a third-party verifier. However, most of these schemes rely on the complicated and resource consuming public key infrastructure (PKI). In this paper, we propose a novel identity-based RDIC scheme, namely Efficient, Dynamic and Identity-based Multiple Replication Provable Data Possession (EDID-MRPDP) without the burden of PKI. We introduce a new construction of Homomorphic Verifiable Tag (HVT) and a novel data structure namely Compressed Authentication Array (CAA), which allow EDID-MRPDP to perform batch verification for multiple data owners and cloud servers simultaneously and efficiently, both from computation and communication aspects. To the best of our knowledge, EDID-MRPDP is the first ID-based RDIC scheme with full dynamic updates and multi-replica batch checking. We provide comprehensive correctness and soundness proofs of EDID-MRPDP. Meanwhile, the detailed performance analyses and simulations show that EDID-MRPDP is practical for large-scale cloud applications.

Secure Dynamic Big Graph Data: Scalable, Low-Cost Remote Data Integrity Checking

As a special type of big data, the big graph has wide applications. The remote data integrity checking (RDIC) scheme enables public clouds to efficiently convince the clients that their graph data are stored properly, without the need of retrieving the actual data contents. The existing schemes support verifiable update often by adopting the authentication data structures (ADSs), e.g., Merkel hash tree (MHT). The main obstacle for applying the existing RDIC schemes to big graphs is due to the lack of support for verifiable sub-graph operations with high efficiency. In this paper, we propose a new RDIC scheme for big graphs, called GVD-RDIC, to support public auditing and verifiable dynamic graph updates with high efficiency. We have designed novel ADS based on the graph Voronoi diagram (GVD) and enhanced MHT to address the integrity of graph structure and verifiable sub-graph updates. In addition, our ADS can be applied to any type of graphs. Moreover, our GVD-RDIC scheme adopts a new construction for the homomorphic authenticator to enable index verifications for public auditors. A server response constructed with unchallenged block will be rejected. The proposed scheme is proven secure under a random oracle model. Both the theoretical analysis and the simulation results show that our scheme is practicable for real-world big graphs.

Identity-Based Remote Data Integrity Checking With Perfect Data Privacy Preserving for Cloud Storage

Remote data integrity checking (RDIC) enables a data storage server, say a cloud server, to prove to a verifier that it is actually storing a data owner’s data honestly. To date, a number of RDIC protocols have been proposed in the literature, but most of the constructions suffer from the issue of a complex key management, that is, they rely on the expensive public key infrastructure (PKI), which might hinder the deployment of RDIC in practice. In this paper, we propose a new construction of identity-based (ID-based) RDIC protocol by making use of key-homomorphic cryptographic primitive to reduce the system complexity and the cost for establishing and managing the public key authentication framework in PKI-based RDIC schemes. We formalize ID-based RDIC and its security model, including security against a malicious cloud server and zero knowledge privacy against a third party verifier. The proposed ID-based RDIC protocol leaks no information of the stored data to the verifier during the RDIC process. The new construction is proven secure against the malicious server in the generic group model and achieves zero knowledge privacy against a verifier. Extensive security analysis and implementation results demonstrate that the proposed protocol is provably secure and practical in the real-world applications.