Outsourced Cloud Data Research Articles

Retraction Note: FSS-SDD: fuzzy-based semantic search for secure data discovery from outsourced cloud data

Retraction Note: FSS-SDD: fuzzy-based semantic search for secure data discovery from outsourced cloud data

REKS: Role-Based Encrypted Keyword Search With Enhanced Access Control for Outsourced Cloud Data

REKS: Role-Based Encrypted Keyword Search With Enhanced Access Control for Outsourced Cloud Data

QSKCG: Quantum‐based secure key communication and key generation scheme for outsourced data in cloud

AbstractIn the era of digital proliferation, individuals opt for cloud servers to store their data due to the diverse advantages they offer. However, entrusting data to cloud servers relinquishes users' control, potentially compromising data confidentiality and integrity. Traditional auditing methods designed to ensure data integrity in cloud servers typically depend on Trusted Third Party Auditors. Yet, many of these existing auditing approaches grapple with intricate certificate management and key escrow issues. Furthermore, the imminent threat of powerful quantum computers poses a risk of swiftly compromising these methods in polynomial time. To overcome these challenges, this paper introduces a Quantum‐based Secure Key Communication and Key Generation Scheme QSKCG for Outsourced Data in the Cloud. Leveraging Elliptic Curve Cryptography, the BB84 secure communication protocol, certificateless signature, and blockchain network, the proposed scheme is demonstrated through security analysis, affirming its robustness and high efficiency. Additionally, performance analysis underscores the practicality of the proposed scheme in achieving post‐quantum security in cloud storage.

Data integrity aware system for executing dynamic operations on outsourced cloud data

The cloud computing platform of today handles a greater amount of real-time data, which requires dynamic data operations. The majority of the currently available cloud techniques, however, do not concentrate on dynamic data operations. Hence, this work provides a system that enables dynamic data operations to be carried out on a cloud computing platform, such as the insertion, deletion, and updating of data. The performance of the work is tested in terms of time consumption with respect to data storage, retrieval, data block insertion and deletion operations. The analysis is carried out by altering the data volume and the performance of the work is satisfactory with reasonable time consumption.

A Blockchain-Based Solution for Ensuring Provenance to Outsourced Cloud Data in a Decentralized Sharing Ecosystem

A Blockchain-Based Solution for Ensuring Provenance to Outsourced Cloud Data in a Decentralized Sharing Ecosystem

Certificateless public auditing scheme with sensitive information hiding for data sharing in cloud storage

In the cloud storage environment, users can store their data on cloud servers to save local storage resources and also share data with other users through cloud servers. Nevertheless, the outsourced data in cloud is vulnerable to tampering or loss due to software or hardware failures, hacker attacks, and other unforeseen issues. Public auditing technique have been developed to safeguard the integrity of the outsourced data. In addition, outsourced data typically contains users’ sensitive information like their names and ages, which are likely to be unavoidably exposed to cloud servers and other users. To tackle the aforementioned issues, a certificateless public auditing scheme with sensitive information hiding (CPAS-SIH) for data sharing is presented in this paper, which introduces a third-party sanitizer to sanitize the data blocks encompassing sensitive information in outsourced data and converts their tags into the valid ones for sanitized data blocks. Meanwhile, an extended double linked list information table is utilized to enable data dynamic operations, including the data blocks modification, insertion, as well as deletion. The security analysis demonstrates that CPAS-SIH satisfies unforgeability, auditing soundness, immutability, and data privacy preservation. The performance evaluation indicates that CPAS-SIH is efficient and practical.

A Role-Based Encryption (RBE) Scheme for Securing Outsourced Cloud Data in a Multi-Organization Context

Role-Based Encryption (RBE) is an emerging new technique that integrates role based access control (RBAC) model with encryption. RBE embeds RBAC access policies in encrypted data itself so that only users belonging to appropriate roles are able to decrypt and access the data. However, the existing RBE schemes have been focusing on the single-organization cloud storage system, where the stored data can be accessed by users of the same organization. This paper presents a novel RBE scheme with efficient user revocation for the multi-organization cloud storage system, where the data from multiple independent organizations are stored and can be accessed by the authorized users from any other organization. Additionally, an outsourced decryption mechanism is introduced which enables the users to delegate expensive cryptographic operations to the cloud, thereby reducing the overhead on the end-users. Security and performance analyses of the proposed scheme demonstrate that it is provably secure against Chosen Plaintext Attack and can be useful for practical applications due to its low computation overhead.

An efficient, secure and verifiable conjunctive keyword search scheme based on rank metric codes over encrypted outsourced cloud data

Public key encryption with keyword search (PEKS) is a cryptographic primitive that allows a secure search for desired keywords of data users by a cloud server using a search token. To the best of our knowledge, we propose the first practical, semantic secure, and post-quantum PEKS scheme based on rank metric codes. The proposed scheme is secure against keyword guessing attack, reaction attack, and key exposure, and enjoys conjunctive keyword search, verifiability of search results using Bloom filter and garbled Bloom filter. We implement the scheme with C++ programming language on a desktop computer. At the security level of 256 bits, the scheme performs all the necessary steps for encryption, keyword search, and verification of search results for one keyword in 22.5 milliseconds. Furthermore, the public key length at this security level is about 5 kilobytes. We show that the scheme is more efficient than the existing relevant post-quantum ones.

ElGamal algorithm with hyperchaotic sequence to enhance security of cloud data

PurposeIn the cloud-computing environment, privacy preservation and enabling security to the cloud data is a crucial and demanding task. In both the commercial and academic world, the privacy of important and sensitive data needs to be safeguarded from unauthorized users to improve its security. Therefore, several key generations, encryption and decryption algorithms are developed for data privacy preservation in the cloud environment. Still, the outsourced data remains with the problems like minimum data security, time consumption and increased computational complexity. The purpose of this research study is to develop an effective cryptosystem algorithm to secure the outsourced data with minimum computational complexity.Design/methodology/approachA new cryptosystem algorithm is proposed in this paper to address the above-mentioned concerns. The introduced cryptosystem algorithm has combined the ElGamal algorithm and hyperchaotic sequence, which effectively encrypts the outsourced data and diminishes the computational complexity of the system.FindingsIn the resulting section, the proposed improved ElGamal cryptosystem (IEC) algorithm performance is validated using the performance metrics like encryption time, execution time, decryption time and key generation comparison time. The IEC algorithm approximately reduced 0.08–1.786 ms of encryption and decryption time compared to the existing model: secure data deletion and verification.Originality/valueThe IEC algorithm significantly enhances the data security in cloud environments by increasing the power of key pairs. In this manuscript, the conventional ElGamal algorithm is integrated with the pseudorandom sequences for a pseudorandom key generation for improving the outsourced cloud data security.

Deterministic Algorithm for Cloud Outsourced Data

Deterministic Algorithm for Cloud Outsourced Data

An Effective and Efficient Framework for Fast Privacy-Preserving Keyword Search on Encrypted Outsourced Cloud Data

Cloud providers offer storage as a service to the data owners to store emails and files on the cloud server. However, sensitive data should be encrypted before storing on the cloud server to avoid privacy concerns. With the encryption of documents, it is not feasible for data owners to retrieve documents based on keyword search as they can do with plain text documents. Hence, it is desirable to perform a multi-keyword search on encrypted data. To achieve this goal, we present a fast privacy-preserving model for keyword search on encrypted outsourced data in this paper. Specifically, the model first performs a keyword search on encrypted data and checks its support for dynamic operations. Based on keyword search results, it then sorts all the relevant data documents using the number of keywords matched for a given query. To evaluate its performance of our model, we applied the standard metrics like precision and recall. The results show the effectiveness of our privacy-preserving keyword search on encrypted outsourced data.

Verifying multiple replica possession with public key segment under public cloud storage environment

AbstractReplication is widely used in cloud storage systems to provide availability and reliability for outsourced cloud data. However, untrusted providers would like to maintain fewer replicas than promise for economic profits or other benefits. Since providers hardly ever offer remote checking tools, it becomes a challenge to validate from user side whether Providers are faithfully keeping enough replicas or not. Existing solutions have several disadvantages, including low efficiency, high computation overload, and lack of supporting for colluding attack. In this article, a collector‐based multiple replica storage model is introduced. Based on that, a novel multiple replica possession proving scheme public key segment is proposed in detail. Particularly, a public key is divided into several private segments, which will be distributed to corresponding storage servers for evidence generation. Only if every replica node shows its correct possession evidence, can the challenge be concluded as success. Theoretical analysis and prototype experiments show the correctness, security, and efficiency of the scheme.

PMAB: A Public Mutual Audit Blockchain for Outsourced Data in Cloud Storage

With the rapid growth of data, limited by the storage capacity, more and more IoT applications choose to outsource data to Cloud Service Providers (CSPs). But, in such scenarios, outsourced data in cloud storage can be easily corrupted and difficult to be found in time, which brings about potential security issues. Thus, Provable Data Possession (PDP) protocol has been extensively researched due to its capability of supporting efficient audit for outsourced data in cloud. However, most PDP schemes require the Third-Party Auditor (TPA) to audit data for Data Owners (DOs), which requires the TPA to be trustworthy and fair. To eliminate the TPA, we present a Public Mutual Audit Blockchain (PMAB) for outsourced data in cloud storage. We first propose an audit chain architecture based on Ouroboros and an incentive mechanism based on credit to allow CSPs to audit each other mutually with anticollusion (any CSP is not willing to help other CSPs conceal data problems). Then, we design an audit protocol to achieve public audit efficiently with low cost of audit verification. Rigorous analysis explains the security of PMAB using game theory, and performance analysis shows the efficiency of PMAB using the real-world dataset.

Secure Data Set Operation Protocols for Outsourced Cloud Data to Protect User Privacy in Smart City

With the rapid development of information technology, internet of things, cloud computing, digital networks and 5G have become an indispensable part of our life. Due to the development of these cutting-edge digital technologies, smart cities now have become a reality. During the development of smart cities, many different sensing devices of the cities would generate lots of data. To smoothly use the massive data, the paradigm of cloud computing will be deployed by smart cities, these data will be efficiently stored and processed by the cloud servers. However, the security of data in smart cities should be guaranteed, especially for the privacy protection of data. Aiming at securely managing cloud data in smart cities, this paper proposes a set of secure cloud data computing protocols for set operations based on the Paillier encryption system. For the rational numbers which are very common in smart cities, we design a coding technology to realize the secure homomorphic computation of them. We also verify the security and correctness of our protocols through rigorous mathematical proof, and demonstrate the efficiency of our solutions by performance analysis.

Retraction: Secure Ring Signature based privacy preserving of Public Auditing mechanism for outsourced data in cloud computing paradigm (J. Phys.: Conf. Ser. 1916 012079)

This article (and all articles in the proceedings volume relating to the same conference) has been retracted by IOP Publishing following an extensive investigation in line with the COPE guidelines. This investigation has uncovered evidence of systematic manipulation of the publication process and considerable citation manipulation.IOP Publishing respectfully requests that readers consider all work within this volume potentially unreliable, as the volume has not been through a credible peer review process.IOP Publishing regrets that our usual quality checks did not identify these issues before publication, and have since put additional measures in place to try to prevent these issues from reoccurring. IOP Publishing wishes to credit anonymous whistleblowers and the Problematic Paper Screener [1] for bringing some of the above issues to our attention, prompting us to investigate further.[1] Cabanac G, Labbé C and Magazinov A 2021 arXiv:2107.06751v1 Retraction published: 23 February 2022

Secure Ring Signature based privacy preserving of Public Auditing mechanism for outsourced data in cloud computing paradigm

Cloud computing offers a high scalable environment for data outsourcing in the cloud. This allows a user to access all the cloud applications of any complexity, without thinking about the limitations of the local system infrastructure. It also provide medium to share the data among others. However originality and authenticity of data that is stored in cloud is an open challenge as it has large provision for data lose and date correction. In order to prevent the outsourced against various challenges, many tradition data auditing mechanism on employing third party auditor has been provided in the literatures with computation and communication capabilities. A portable data management system to will be able to perform auditing process, so that we can ensure the accuracy of the data which is stored on a unreliable third party server. This process is done without even, retrieving all the data. Despite of various advantage of public auditing, preserving the identity privacy from third party auditor has become vital task for the current research. In this paper, we have proposed a reliable and secure ring signature for preserving the privacy of data that is outsourced and shared, using public auditing in the computing paradigm. In this work, ring signature is exploited to privacy preserving of the data auditing of common outsourced data. Further the idea of ring-signatures has to be used to build the authenticator on each block of the data that is outsourced, while keeping maintaining the authenticity of the shared-data to be audited. Finally this model can support multi auditing task simultaneously. Experimental analysis on the proposed system proves that it is more secure and highly efficient against data based attacks. Evaluation the performance of the proposed model has been validated that it outperforms state of arts approaches on computation cost and time.

A Blockchain Approach to Ensuring Provenance to Outsourced Cloud Data in a Sharing Ecosystem

Cloud servers offer data owners the opportunityto upload and store encrypted data that several data users can access. However, after outsourcing data to the cloud, data owners have limited control of their data, and external systems are incorporated to manage it. Several research-based solutions use encryption techniques to prevent unauthorized access to the data but ignore the challenge of maintaining the trace of valid changes applied to the data. Provenance data can be used to ascertain the integrity of data and, therefore, should be immutable and secured from adversaries since it contains private information. This article proposes an efficient way of securing access logs by leveraging blockchain. A generic framework is designed, tested, and evaluated, with results showing our model can effectively enhance the security of provenance data. This work considers two categories of data users and account for the distinct roles and permitted actions on the outsourced data. In summary, this work ensures that the data is trustworthy, and verification and management of the outsourced data are assured. Experimental results illustrate the efficiency and scalability of our solution.

Euclidean Distance Based Similarity Measurement and Ensuing Ranking Scheme for Document Search from Outsourced Cloud Data

In this paper, we propose the Euclidean Distance based Similarity Measurement and Ensuing Ranking (EDSMER) scheme to aid effective document search from outsourced cloud data. It is another attempt to find an alternative to binary based approaches. In this approach, the User or the Data owner needs to filter out the suitable keywords for the document and then the index is prepared. To provide security and privacy, both the data and the index are encrypted and moved to the cloud space. The application of Euclidean Distance based Similarity Measurement and Ensuing Ranking (EDSMER) scheme for document searching takes place after the authorized user requests for the documents through query terms. Initially the authorized user sends a query to Cloud Service Provider to retrieve all the documents which are mapped with the keywords provided by him. The proposed algorithm calculates the distance between the query terms and the index terms. The minimum the distance, the more it is closer towards each other and vice-versa. Our Euclidean Distance based Similarity Measurement and Ensuing Ranking (EDSMER) scheme greatly enhances the system functionality by sending the most relevant documents instead of transmitting all documents back. The experimental validations are performed on RFC and FIRE dataset. Through experimental analysis, we prove that our proposed approach is secure and efficient as well as exhibits better recall and precision rate in the IR system to deal with the document-retrieval process.

QShield: Protecting Outsourced Cloud Data Queries With Multi-User Access Control Based on SGX

Due to the concern on cloud security, digital encryption is applied before outsourcing data to the cloud for utilization. This introduces a challenge about how to efficiently perform queries over ciphertexts. Crypto-based solutions currently suffer from limited operation support, high computational complexity, weak generality, and poor verifiability. An alternative method that utilizes hardware-assisted Trusted Execution Environment (TEE), i.e., Intel SGX, has emerged to offer high computational efficiency, generality and flexibility. However, SGX-based solutions lack support on multi-user query control and suffer from security compromises caused by untrustworthy TEE function invocation, e.g., key revocation failure, incorrect query results, and sensitive information leakage. In this article, we leverage SGX and propose a secure and efficient SQL-style query framework named QShield. Notably, we propose a novel lightweight secret sharing scheme in QShield to enable multi-user query control; it effectively circumvents key revocation and avoids cumbersome remote attestation for authentication. We further embed a trust-proof mechanism into QShield to guarantee the trustworthiness of TEE function invocation; it ensures the correctness of query results and alleviates side-channel attacks. Through formal security analysis, proof-of-concept implementation and performance evaluation, we show that QShield can securely query over outsourced data with high efficiency and scalable multi-user support.

Privacy preserved secured outsourced cloud data access control scheme with efficient multi-authority attribute based signcryption

Privacy preserved outsourced data access control is a hard task under the control of third–party storage server. To overcome obstacles in the third party based scenario, Attribute-based signcryption system with bilinear pairing tool is one of the most suitable methods in cloud. It maintains the basic features of security like, authenticity, confidentiality, public verifiability, owner privacy, etc. Although, this method has some challenges like a centralized authority used for user secret key generation for de-signcryption operation, and lack in competent attribute revocation. To overcome the issues, we have proposed a scheme of attribute revocable privacy preserved outsourced based data access control mechanism using Attribute-based signcryption. The proposed method allows multi-authorities for assigning both attribute and secret keys for users along with trusted certified authority, which provides security parameters. The analysis of the proposed method shows less computation cost in decryption and authentication verification. The almost same performance and efficiency is found while comparing with the existing schemes after adding new features.