Cloud Storage Environment Research Articles

Traitor Traceable and Revocation-oriented Attribute Based Encryption with Proxy Decryption for Cloud Devices

Cloud storage environment permits the data holders to store their private data on remote cloud computers. Ciphertext Policy Attribute Based Encryption (CP-ABE) is an advanced method that assigns fine-grained access control and provides data confidentiality for accessing the cloud data. CP-ABE methods with small attribute universe limit the practical application of CP-ABE as the public parameter length linearly increases with the number of attributes. Further, it is necessary to provide a way to perform complex calculations during decryption on outsourced devices. In addition, the state-of-art techniques found it difficult to trace the traitor as well as revoke their attribute due to the complexity of ciphertext updation. In this paper, a concrete construction of CP-ABE technique has been provided to address the above limitations. The proposed technique supports large attribute universe, proxy decryption, traitor traceability, attribute revocation and ciphertext updation. The proposed scheme is proven to be secure under random oracle model. Moreover, the experimental outcomes reveal that our scheme is more time efficient than the existing schemes in terms of computation cost.

Searchable Encryption Scheme for Large Data Sets in Cloud Storage Environment

Searchable Encryption Scheme for Large Data Sets in Cloud Storage Environment

Enhancing cloud data security: User-centric approaches and advanced mechanisms

Cloud storage has led to a transformative era of data management for organizations, but this paradigm shift has also introduced critical security challenges. This paper is motivated by the urgent need to strengthen cloud data security against unauthorized access and breaches. Our investigation revolves around the vulnerabilities stemming from distributed links in cloud storage, shedding light on the paramount importance of safeguarding crucial commercial records. These challenges encompass the menace posed by both external attackers and unscrupulous customers, amplified within the complex landscape of multi-tenant architectures. This work presents the Secure-Cloud-Guard algorithm to achieve these goals—a multifaceted approach integrating encryption, biometric authentication, and MAC address security mechanisms. The Secure-Cloud-Guard algorithm, rooted in the user-centric paradigm, enhances data protection in cloud storage environments by orchestrating multiple layers of security. The algorithm’s simulation involves thorough evaluation through encryption performance analysis, biometric authentication testing, and MAC address security validation. The simulation results reveal the effectiveness of our proposed algorithm. Encryption performance metrics showcase the encryption throughput and latency, thereby gauging the efficiency of the encryption process. The biometric authentication simulation calculates the false acceptance rate (FAR) to determine the algorithm’s accuracy and false rejection rate (FRR). The simulation of MAC address security illustrates the algorithm’s ability to authenticate devices through MAC addresses, providing insights into its authentication success rate (ASR). In conclusion, an, aligning with user-centric approaches and incorporating advanced mechanisms, such as encryption, biometric authentication, MAC address security, contribute to the ongoing efforts of fortifying the security landscape of cloud storage and computing

Integrating IoT with WSNs using fuzzy logic-based middleware

With the rapid adoption of cloud storage for business and personal use, data security has become a significant concern. This study investigates the effectiveness of advanced encryption algorithms to ensure the integrity, confidentiality, and availability of data stored in cloud environments. The research focuses on the implementation and evaluation of three encryption algorithms: AES-256, ChaCha20, and Threefish, comparing their performance in terms of computational complexity, key generation, and resistance to various attacks. The study utilizes a testbed consisting of a simulated cloud storage environment, where the encryption algorithms are deployed and assessed based on encryption/decryption time and throughput. Results indicate that the ChaCha20 algorithm outperforms both AES-256 and Threefish in terms of encryption/decryption speed while maintaining strong security. Moreover, the findings suggest that the combination of these encryption algorithms can enhance data security by providing a multi-layered defense mechanism against potential threats. The research contributes to the advancement of cloud storage security by identifying optimal encryption algorithms and proposing a robust solution for safeguarding sensitive information.

Revocable-Attribute-Based Encryption with En-DKER from Lattices

Cloud computing offers abundant computing resources and scalable storage, but data leakage in the cloud storage environment is a common and critical concern due to inadequate protection measures. Revocable-attribute-based encryption (RABE) is introduced as an advanced form of identity-based encryption (IBE), which encrypts sensitive data while providing fine-grained access control and an effective user revocation mechanism. However, most existing RABE schemes are not resistant to quantum attacks and are limited in their application scenarios due to the revocation model. In this paper, we propose a RABE scheme constructed from lattices. Our scheme has several advantages, including a near-zero periodic workload for the key generation center (KGC), ensuring scalability as the number of users increases. Additionally, the encryptor is relieved from managing a revocation list. Moreover, our scheme guarantees the confidentiality and privacy of other ciphertexts even if the decryption key for a specific period is compromised. We validated the correctness of our scheme and demonstrated its security under the assumption of learning with errors (LWE), which is widely believed to be resistant to quantum attacks. Finally, we provide an application example of our RABE scheme in the electronic healthcare scenario.

Effective Cost Reduction Usage of Infrastructure in Small Scale Sectors using Cloud Storage and Internet of Things

Presently many small-scale information technology based private sectors are scare due to spending of high cost for maintaining of infrastructures and resources. In order to avoid to pay more money on maintaining infrastructures, there is a need of an effective price reduction method for the usage of infrastructures in various computer-based private sectors which has been achieved through integration of different online and offline cloud storages along with internet of things sensors. This method delivers huge range of infrastructures, resources and services through online and offline platforms through on-demand basics of user request. This system disables or switch off unnecessary services or resources when it is unused by people in the private sectors which has been controlled through various types of sensors. This integrated cloud storage and IoT method verifies user verification and validation along with storing all information about status of infrastructures in offline and online cloud storage environment. This paper deals dynamic group audit regulation through k-means cluster technique with cryptographic algorithm. The alert messaging and alarm indication system has been enforced in this system. Combining of internet of things and cloud storage techniques which guarantees reduction of cost for usage of infrastructures and also assures privacy, security on quality of service with maintaining of better information transmission. This high skilled method preserves the internet of things with cloud storage environment with better performance evaluation in terms of bandwidth usage and computational and communication cost.

An Efficient Attribute-Based Encryption Scheme with Data Security Classification in the Multi-Cloud Environment

As an increasing number of people and corporations move their data to the cloud side, how to ensure efficient and secure access to data stored on the cloud side has become a key focus of current research. Attribute-Based Encryption (ABE) is largely recognized as the best access control method for safeguarding the cloud storage environment, and numerous solutions based on ABE have been developed successively. However, the majority of current research is conducted within a single cloud provider, and only the limited number of schemes for the multi-cloud environment also fail to support the data security classification on the cloud side. Therefore, we propose an efficient attribute-based encryption scheme with data security classification in the multi-cloud environment. In our scheme, the data owner’s data are divided into two security levels and stored in different cloud providers, which improves the security of outsourcing data. Moreover, based on Ciphertext-Policy Attribute-Based Encryption (CP-ABE), our scheme can not only provide a fine-grained access control for the data user, but also completely exploit the cloud side to facilitate outsourcing decryption to lighten the data user’s computing load. The security analysis showed that our scheme is effective against selective-attribute plaintext attack, as well as protects the privacy of the data. The experimental results also demonstrated that the computational overhead is obviously less than other existing schemes.

Framework for Data Provenance Assurance in Cloud Environment using Ethereum Blockchain

Ensuring secure data provenance is crucial for maintaining accountability and confidentiality in cloud environments. Cloud data provenance involves recording the history of creation and operations performed on cloud data objects. However, establishing trust between cloud customers and service providers remains a challenge, highlighting the need for assured data provenance models in cloud storage. Blockchain technology has emerged as a solution for designing data provenance assurance mechanisms. It provides a decentralized and distributed ledger to record the provenance of digital assets. In this context, we present a blockchain-based framework for ensuring data provenance in cloud storage. Initially, we develop a cloud storage application using OpenStack swift storage. This application caters to the storage needs of university students and faculty while providing data provenance capabilities. Subsequently, we design a data provenance assurance framework for confidential files of users using the Ethereum blockchain. To evaluate the scalability and performance of the proposed framework, we analyze various factors such as transaction throughput, latency, network size, and load on the blockchain network. The performance of the system is compared under two consensus algorithms: Proof of Work and Proof of Authority. By conducting this analysis, we aim to assess the effectiveness and efficiency of the blockchain-based solution in ensuring data provenance in cloud storage environments.

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 Secured Data Storage in Cloud Computing by Using Block Design Based Key Agreement

Cloud computing has emerged as a dominant paradigm for storing and accessing data. In group data sharing scenarios, where multiple users collaborate and exchange sensitive information in the cloud, ensuring secure and efficient key agreement becomes crucial. This paper presents a comprehensive analysis of key agreement mechanisms for group data sharing in cloud computing environments. We explore various cryptographic techniques and protocols specifically designed for establishing secure communication channels among group members. The paper discusses the challenges associated with key agreement in the cloud, proposes potential solutions, and provides insights into the implementation and evaluation of such mechanisms. The proposed framework aims to protect data confidentiality, integrity, and availability, ensuring a robust and reliable cloud storage environment. We explore various cryptographic techniques, including encryption, key management, and authentication mechanisms, and discuss their application in securing cloud-based data storage. The framework addresses common security threats and provides guidelines for implementing a secure cloud storage solution.

Multiauthority Attribute-Based Encryption for Assuring Data Deletion

In order to alleviate key escrow issue, the notion of multiauthority attribute-based encryption (MA-ABE) was presented, which was widely applied in cloud storage environment. In data sharing environment, secure data deletion is very crucial and challenging issue. Hence, in this article, we concentrate on verification of data deletion operation, i.e., assuring data deletion. To solve this problem, we put forward a system model, formal definition and security model of MA-ABE for assuring data deletion. Furthermore, we design a MA-ABE scheme for assuring data deletion, which is more practicable than the single authority ABE scheme. The designed scheme not only overcomes key escrow issue, but also resists collusion attack between malicious user and unauthorized user. In addition, our scheme utilizes merkle hash tree to obtain verifiable data deletion. Based on decisional bilinear Diffie-Hellman (DBDH) assumption, the scheme is proven to be secure under the selective-policy model. The experimental result indicates that the designed scheme is efficient for practical application.

SM2-Based Offline/Online Efficient Data Integrity Verification Scheme for Multiple Application Scenarios.

With the rapid development of cloud storage and cloud computing technology, users tend to store data in the cloud for more convenient services. In order to ensure the integrity of cloud data, scholars have proposed cloud data integrity verification schemes to protect users' data security. The storage environment of the Internet of Things, in terms of big data and medical big data, demonstrates a stronger demand for data integrity verification schemes, but at the same time, the comprehensive function of data integrity verification schemes is required to be higher. Existing data integrity verification schemes are mostly applied in the cloud storage environment but cannot successfully be applied to the environment of the Internet of Things in the context of big data storage and medical big data storage. To solve this problem when combined with the characteristics and requirements of Internet of Things data storage and medical data storage, we designed an SM2-based offline/online efficient data integrity verification scheme. The resulting scheme uses the SM4 block cryptography algorithm to protect the privacy of the data content and uses a dynamic hash table to realize the dynamic updating of data. Based on the SM2 signature algorithm, the scheme can also realize offline tag generation and batch audits, reducing the computational burden of users. In security proof and efficiency analysis, the scheme has proven to be safe and efficient and can be used in a variety of application scenarios.

CADF-CSE: Chaotic map-based authenticated data access/sharing framework for IoT-enabled cloud storage environment

Data is an essential asset of an organization or individual in this information age. Secure and resource-efficient data communication has become paramount in the IoT-enabled cloud storage environment. The users must communicate with the cloud storage servers to access, store, and share the data utilizing the public communication channel, which is exposed to various security threats. Moreover, various security frameworks have been presented to render secure data access, storage, and sharing functionalities for the cloud storage environment. Most of them are complicated and incapacitated of resisting various security attacks. Thus, it is imperative to design a secure and resource-efficient data access, storage, and sharing framework for the cloud storage environment. This paper presents a chaotic map-based authenticated data access/sharing framework for the IoT-enabled cloud storage environment (CADF-CSE). CADF-CSE is designed using the chaotic map, authenticated encryption scheme (AEGIS), and one-way hash function (Esch256). The proposed CADF-CSE comprises three significant phases user access control, data storage, and data sharing. The user access control phase enables the user and cloud server to attain mutual authentication followed by the secret session key establishment. Using the established SK during the access control phase user and cloud server exchange information securely across the public Internet. The data storage phase facilitates the data owner to store the data on a cloud server in encrypted form, where encryption is performed with a secret key derived from the user’s biometric. The data-sharing phase enables users to access the data from the cloud server after acquiring mutual permission from the cloud server and the data owner. In addition, an explication of the CADF-CSE through formal and informal analysis shows its resilience to various security attacks. Finally, the performance comparison explicates that CADF-CSE renders better security features while requiring lower computational and communication costs than the related security frameworks.

Verifiable Keyword Search Encryption Scheme That Supports Revocation of Attributes

In recent years, searchable encryption technology and attribute encryption technology have been widely used in cloud storage environments, and attribute-based searchable encryption schemes can both achieve the retrieval of encrypted data and effectively solve the access control problem. Considering that existing attribute-based searchable encryption schemes for cloud storage only support keyword search and do not support attribute revocation, most of the schemes that support attribute revocation only consider the computational overhead of users and ignore the large amount of computational resources consumed by attribute authorization centers when updating keys. In addition, keyword search may lead to partial errors in the returned search results, leading to the wastage of computational and broadband resources. To solve these issues, this paper proposes an attribute-based searchable encryption scheme that supports attribute revocation and is verifiable. To realize fine-grained ciphertext search of encrypted data, support scenarios of dynamic changes of user attributes, and ensure that third-party servers perform the search process reliably and honestly while minimizing computation and storage costs, first, this paper implements attribute revocation with the attribute authorization center by creating a user revocation list and an attribute key revocation list. At the same time, the system updates the attribute key at the time of user search request, which effectively reduces the computational overhead. Second, a third-party auditor is introduced to ensure the correctness of the search results. Finally, the security of this paper is verified by theoretical analysis, and the efficiency and practicality of this paper are verified by comparing it to other schemes through simulation experiments.

Data Rights Confirmation Scheme Based on Auditable Ciphertext CP-ABE in the Cloud Storage Environment

Advances in information technology have made data accessible anytime and anywhere. Currently, data confirmation is a popular area of research. Many current approaches to data confirmation rely on submitting certificates of ownership, embedding digital watermarks, or using blockchain. However, none of these approaches can avoid exposing source data to third parties that are not fully trusted. To address this issue, this paper proposes a new data confirmation method based on ciphertext policy attribute-based encryption (CP-ABE), which is widely used in cloud storage environments. The unique identifier of the data owner is encrypted by Paillier encryption and embedded into the ciphertext, so that the ownership corresponding to the plaintext is converted to the ownership corresponding to the ciphertext. During the entire confirmation process, third-party organizations cannot access the source data, reducing the risk of source data leakage. Finally, the feasibility of the scheme is proved by security proof and experiment comparison.

Retracted: Hybrid Encryption Algorithm for Sensitive Information of College Physical Fitness in Cloud Storage Environment

Retracted: Hybrid Encryption Algorithm for Sensitive Information of College Physical Fitness in Cloud Storage Environment

A Lightweight and Efficient Remote Data Authentication Protocol Over Cloud Storage Environment

Cloud storage services need cost-effective, independent, and scalable functionality to manage data. Cloud repositories provide an opportunity to manage and access essential data conveniently. This article proposes a secure authentication protocol to resolve these issues. To add a convenient sharing of data controlled by a data delegator, we use symmetric encryption and decryption algorithms in which cloud servers encrypt and decrypt the data to control the accessibility of the user. Furthermore, informal security analysis demonstrates that our devised protocol is robust enough to resist various attacks. We present the formal analysis of security using the Random Oracle Model (ROM) to evaluate and prove the security strength of the devised protocol. The proposed and related protocols have been implemented on an online cloud server named PythonAnywhere with PyCrypto and Time libraries using Python with the help of a system that has predefined specifications to compare the performance. The results show that our scheme has feasible computation, storage, communication, and energy efficiency compared to various related protocols.

Health Data Deduplication Using Window Chunking-Signature Encryption in Cloud

Due to the development of technology in medicine, millions of health-related data such as scanning the images are generated. It is a great challenge to store the data and handle a massive volume of data. Healthcare data is stored in the cloud-fog storage environments. This cloud-Fog based health model allows the users to get health-related data from different sources, and duplicated information is also available in the background. Therefore, it requires an additional storage area, increase in data acquisition time, and insecure data replication in the environment. This paper is proposed to eliminate the de-duplication data using a window size chunking algorithm with a biased sampling-based bloom filter and provide the health data security using the Advanced Signature-Based Encryption (ASE) algorithm in the Fog-Cloud Environment (WCA-BF + ASE). This WCA-BF + ASE eliminates the duplicate copy of the data and minimizes its storage space and maintenance cost. The data is also stored in an efficient and in a highly secured manner. The security level in the cloud storage environment Windows Chunking Algorithm (WSCA) has got 86.5%, two thresholds two divisors (TTTD) 80%, Ordinal in Python (ORD) 84.4%, Boom Filter (BF) 82%, and the proposed work has got better security storage of 97%. And also, after applying the de-duplication process, the proposed method WCA-BF + ASE has required only less storage space for various file sizes of 10 KB for 200, 400 MB has taken only 22 KB, and 600 MB has required 35 KB, 800 MB has consumed only 38 KB, 1000 MB has taken 40 KB of storage spaces.

Distributed integrity and non-repudiation scheme in the dynamic vehicular cloud environment

Data storage is one of the major applications of vehicular cloud computing (VCC) where the data is shared concurrently among many vehicles participating in vehicular communications. Integrity and non-repudiation are some of the important security challenges encountered during the provisioning of data storage services. This paper proposes an integrity and non-repudiation verification scheme in a dynamic vehicular cloud storage environment. Vehicle authentication is performed by employing Boneh-Lynn-Shacham (BLS) short signature mechanism. The cryptographic hash function and bitwise exclusive-OR (XOR) operation provide data integrity checking of messages which are uploaded from the vehicle to the cloud. RSU acts as a trusted verifier for data transactions. We evaluated the efficiency of the proposed scheme against standard attacks such as replay attack and tampering attack. Extensive simulations are carried out and the results are compared to ID-based cryptographic schemes. The scheme proposed achieved better in terms of computation overhead, average throughput and communication overhead.

Hybrid Encryption Algorithm for Sensitive Information of College Physical Fitness in Cloud Storage Environment

In order to improve the security of college sports fitness sensitive information, this paper proposes a hybrid encryption algorithm for college sports fitness sensitive information in cloud storage environment. Build an analysis model of influencing factors of cloud storage environment to identify the risk value of sensitive information; Using Bloom filter data structure to eliminate redundant data of sensitive information; The transmission channel model of sensitive information and the security coding model of sensitive information are constructed. Combined with the fuzzy differential information fusion method, the complete key of sensitive information under the symmetric encryption protocol is obtained to realize the key optimization design. Through AES encryption and decryption algorithm, the anti encryption control and structural reorganization of college sports fitness sensitive information, and the iterative convergence control of hybrid encryption, so as to realize the hybrid encryption of college sports fitness sensitive information. The encryption time of the design algorithm under different attribute numbers is always kept below 0.2S, the maximum encryption time under different number of software packages is only 0.5 s, and the encryption accuracy can reach 1, which proves that the design algorithm has certain application value.