Cloud Data Access Research Articles

Verifiable Cloud Data Access: Design, Analysis, and Implementation

In this article, we consider the following cloud storage security problem: A user outsources his/her data to a cloud and later frequently updates the data by adding new data items and deleting existing ones. When the user requests an existing data item from the cloud, the cloud may claim that there is no such data item. This could happen due to cloud management issues, hardware/software failures, hackers, or economic incentives, such as saving cloud’s operation costs. The ability to confirm the data existence/nonexistence when accessing a data item on the dynamic outsourced cloud storage is referred to as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dynamic verifiable data access</i> (DVDA). Existing cloud security research works, including encrypted search and proof of storage (i.e., proof of retrievability and proof of data possession), are not sufficient for addressing dynamic verifiable data access. In this article, we present a solution for the dynamic verifiable data access problem. In order to support data dynamics and verifiability, we enhance a hash authentication tree that is build on top of a hash table with a new semantics. With the enhanced hash authentication tree, the proposed protocol supports adding/deleting data in the outsourced storage while satisfying data access verifiability requirement simultaneously. Our open-source experimental evaluation shows that it only takes less than 0.1 ms to verify a data access on a dataset with 400 items using communication cost around 1.7 KB.

Modified Chebyshev polynomial-based access control mechanism for secured data access in cloud computing environment

Cloud computing is a popular model for offering infinite storage resources for the users. In the present scenario, extremely sensitive data is stored in the third-party cloud service provider’s infrastructure. For instance, patients who have direct access to the healthcare system may access the cloud-based health care data at any time based on the needs. Such sensitive data is subjected to various security issues because of the entities from multiple hosts connecting to cloud storage. In the proposed work, an optimized secured data access control mechanism named as modified Chebyshev polynomial-based access control (MCPAC) is presented. In MCPAC scheme, multiple levels of verification and authentications are carried out to provide resilience against widely recognized attacks. The proposed access control scheme is evaluated in a real private cloud infrastructure using the metrics, such as precision, recall and detection rate. It is proved that the proposed MCPAC offers better privacy protection with the precision of 0.8947, recall of 0.8983, and detection rate of 85.63%, which is high as compared to the conventional state-of-the-art methods. Security analysis is also done for the MCPAC scheme, and it indicates that the system efficiently handles the well-known attacks. The performance analysis shows that MCPAC meets the essential security mandates and excels in computational efficiency by making it suitable for the realistic applications hosted in a cloud computing environment.

Game Theoretical Analysis on Acceptance of a Cloud Data Access Control System Based on Reputation

With the rapid development of the Internet, cloud storage has penetrated into every aspect of human society. However, cloud data disclosure happens more and more frequently, which makes cloud data security and privacy protection impact wide adoption of cloud storage. Control cloud data access based on reputation by introducing a Reputation Center (RC) was proposed and demonstrated to secure cloud data effectively in [9] . But the acceptance of such a system by cloud users and Cloud Service Providers (CSPs) is crucial for its practical deployment and final success. In this paper, we investigate the acceptance of a cloud data access control system based on reputation using Game Theory. Due to the existence of dishonest CSPs, there exists a social reputation dilemma among CSPs, which seriously impedes the popularity of cloud storage. To encourage users to use cloud storage and suppress collusion between CSPs and data requesters, a repeated public-goods game is built up by applying a compensation mechanism to improve the utilities of cloud users and a punishment mechanism based on reputation to incent honest behaviors. Theoretical analysis and simulation results show the effectiveness of the compensation and punishment mechanisms to increase cloud storage rate and restrain dishonest system entities.

Unified Biometric Privacy Preserving Three-Factor Authentication and Key Agreement for Cloud-Assisted Autonomous Vehicles

Autonomous vehicles (AVs) are increasingly common, although there remain a number of limitations that need to be addressed in order for their deployment to be more widespread. For example, to mitigate the failure of self-driving functions in AVs, introducing the remote control capability (which allows a human driver to operate the vehicle remotely in certain circumferences) is one of several countermeasures proposed. However, the remote control capability breaks the isolation of onboard driving systems and can be potentially exploited by malicious actors to take over control of the AVs; thus, risking the safety of the passengers and pedestrians (e.g., AVs are remotely taken over by terrorist groups to carry out coordinated attacks in places of mass gatherings). Therefore, security is a key, mandatory feature in the design of AVs. In this paper, we propose a cloud-centric three-factor authentication and key agreement protocol (CT-AKA) integrating passwords, biometrics and smart cards to ensure secure access to both cloud and AVs. Three typical biometric encryption approaches, including fuzzy vault, fuzzy commitment, and fuzzy extractor, are unified to achieve three-factor authentication without leaking the biometric privacy of users. Moreover, two session keys are negotiated in our protocol, namely: one between the user and AV to support secure remote control of the AV, and the other is negotiated between the mobile device and the cloud to introduce resilience to the compromise of ephemeral security parameters to ensure cloud data access security with a high security guarantee. Finally, we formally verify the security properties and evaluate the efficiency of CT-AKA, whose findings demonstrate that the protocol achieves high security strength with reasonable computation and communication costs.

Suppressed K-Anonymity Multi-Factor Authentication Based Schmidt-Samoa Cryptography for privacy preserved data access in cloud computing

Security and privacy-preservation is a significant problem to be solved in the cloud when accessing data services. The existing authentication technique verifies the client identity using single authentication factor. But, the performance of conventional single factor authentication technique is not efficient since the client’s sensitive information is highly intrusive and exposed to third parties. In order to overcome these limitations, a novel multifactor authentication called Suppressed K-Anonymity Multi-Factor Authentication Based Schmidt-Samoa Cryptography (SKMA-SC) technique is proposed. The SKMA-SC technique comprises three key processes namely registration, authentication and data access. During the registration phase, the clients register their personal identification information’s and securely stores it in the cloud server (CS) with support of suppression method. This helps for SKMA-SC technique to preserve the client sensitive information’s from adversaries or third parties in a cloud environment. During the authentication phase, SKMA-SC technique validates the identity of clients by considering multifactor such as password, one-time token and conditional attributes. At last in the data access phase, SKMA-SC technique allows the clients to get requested data services when she or he is authorized by performing Schmidt-Samoa data encryption/decryption process . From that, SKMA-SC technique avoids illegal access from the unauthorized party over insecure communications in a cloud environment with a lower amount of time. Result analysis of SKMA-SC technique is carried out with the metrics authentication accuracy (AA), computational complexity (CC) and privacy-preserving rate (PPR) with different number of clients and cloud data. The experimental result proves that SKMA-SC technique enhances the PPR and lessens the CC of authentication as evaluated with state-of-the-art works.

Managing Cloud Data Integrity and Access Control Mechanism through Blockchain

Managing Cloud Data Integrity and Access Control Mechanism through Blockchain

Flexible Data Access Control using Attribute-Based Encryption and Proxy Re-Encryption in Cloud Computing

In the fast-paced business world of today, the adoption of the latest technological advances is essential for sustainability and growth. One such area of technology where more and more businesses are taking advantage of is the cloud, which allows data to be stored remotely on servers across the world. Cloud storage also gives companies greater flexibility with their data and information, as it can be accessed anywhere and anytime, which can be especially helpful for businesses that operate in many countries. Despite all the advantages, due to problems such as lack of standardization, there are unfortunately some drawbacks and security issues that can arise from using cloud computing and SaaS services (Software-as-a-service). Controlling private and delicate data on the cloud is becoming a serious issue. In this work to ensure integrity and authenticity, the proposed model which is capable of providing data access control to the cloud data. Trust plays a vital role in data sharing among the users of the cloud. This work powerfully handles data access in cloud computing focused on trust assessed by the data owner or reputations produced by several reputations center’s flexibly by relating Attribute-Based Encryption and Proxy-based Re-Encryption. Context-aware trust and reputation assessment are used to support various control scenarios and strategies.

Securing Personal Health Records using Advanced Multi-Factor Authentication in Cloud Computing

Cloud computing is a novel prototype to provide services via the internet. Most of the fields like banking, industries, educational institutions, and healthcare are storing their applications, data and accessing it through cloud because of its versatility and affordable price. Even though cloud has a many special feature, data security and privacy are the most important issues in a cloud background. Especially in healthcare sector, according to recent report numerous amount of healthcare data breached by unknown websites and hackers, and much healthcare information breaches are occurring around the world for different purposes and still it is vulnerable on account of storing and accessing data through third party cloud servers. Due to many attacks on personal health records data security and privacy in cloud environment, it is a primary task to concentrate on solving this issue because such health information are really sensitive, and playing vital role in decision-making of patients health which wrong decision may spoil patient’s health, life along with health institution’s reputation. To ensure security and privacy, data encryption and authentication are the key technologies which are a technique to secure data and create proof identities to obtain access of data in the system. Conventional password authentication does not provide sufficient security for information to the new means of attacks. So, this paper introduces a framework for data encryption using standard RSA and Hash function and advanced multi factor authentication technique to cloud data access which authenticates the user based on different factors such as contextual, signcryption and iris bio-metric features. This prototype to cloud computing is implemented using open source technology. The proposed advanced system minimizes intermediate data access due to the complexity of key access and strong authentication. The performance of the system has been evaluated using experimental results such as encryption and decryption time, authentication accuracy, execution time.

DAIS: dynamic access and integration services framework for cloud-oriented storage systems

This paper proposes a framework named Dynamic Access and Integration Services (DAIS) framework. The framework provides on-demand and large scale integrated data access in cloud computing environment. The sole motivation of this research paper is to enhance the performance of Cloud-Oriented Storage (COS) systems. DAIS framework consists of two basic modules namely (1) Adjacency COS Overlay Topology (ACOT) and (2) Cloud Storage Resource Discovery (CSRD). ACOT introduces a self-organizing well balanced m-way tree which removes the necessity of centralized approaches and adopts dynamic and scalable data access in cloud computing environment. CSRD module provides data integration mechanism and efficient resource discovery from geographically distributes COS systems. In this paper, Hadoop test-bed setup has been deployed for experiment and results analysis. All input and output data have been collected in the Hadoop Distributed File System (HDFS). In the experiments, performance, bandwidth and energy efficiency of the proposed DAIS framework have been demonstrated and compared with three different approaches like, Static DAIS, P2P and DSSM. To make it energy efficient, measurement unit and its mathematical model have been defined. Energy efficiency results have been compared with two popular approaches HBase and Hadoop-MR, and found better in most of the cases.

An attribute-based lightweight cloud data access control using hypergraph structure

Cloud file storage systems are the current trend of enterprises and also of individual users. Due to the malicious or unauthorized users, file sharing among the cloud users has become the biggest challenge in the recent times. Attribute-based signcryption (ABSC) is known as the versatile cryptographic primitive which achieves the fine-grained access control over robust cloud storage. ABSC combines attribute-based encryption (ABE) and attribute-based signatures to achieve privacy-oriented confidentiality along with the authenticity. Unfortunately, most of the present ABE and ABSC schemes leverage heavy computational overheads against the key length, the ciphertext size or the expressive access structures used. In this paper, a new ABSC scheme is devised to reduce computational overheads, more particularly, at cloud by introducing the more expressive hypergraph access structure, Attribute HyperGraph. On a positive note, the proposed system outperforms and shows less cloud computational timing without exponentiations unlike Deng et al. (IEEE Access 6:39473–39486, 2018. https://doi.org/10.1109/ACCESS.2018.2843778 ), Liu et al. (Future Gener Comput Syst 52:67–76, 2015. https://doi.org/10.1016/j.future.2014.10.014 ) and Li et al. (IEEE Trans Parallel Distrib Syst 25(8):2201–2210, 2014. https://doi.org/10.1109/TPDS.2013.271 ) schemes. Subsequently, the system does not incur any cryptographic computations associated with designcryption at cloud unlike Deng et al. (2018).

EC(DH)&lt;SUP align="right"&gt;2&lt;/SUP&gt;: an effective secured data storage mechanism for cloud based IoT applications using elliptic curve and Diffie-Hellman

In the rapid growth of cloud computing with internet of things (IoT) technology utilisation in this fast world, security is an essential issue in cloud data storage and access the encrypted data. In the past, several researchers have worked on data storage mechanisms and came up with different ideas to fulfil the cloud user's expectation. Even though, they have failed to provide the sufficient security on cloud. For providing better security over the cloud, we propose a new elliptic curve and Diffie-Hellman based data storage mechanism called EC(DH)2. Here, the standard Diffie-Hellman algorithm is used twice as DH2 and it is combined with the standard elliptic curve cryptographic algorithm for performing secured storage in cloud based IoT applications. The experiments have been conducted by using the various sizes of documents and files for evaluating the proposed EC(DH)2 algorithm and is proven that it provides better protection and increased key size.

Secure hash algorithm-based multiple tenant user security over green cloud environment

This paper proposes a green cloud multi-tenant trust authentication with secure hash algorithm-3 (GreenCloud-MTASHA3) scheme to eliminate the unauthorised tenant access. GreenCloud-MTASHA3 scheme provide security over the multiple tenant requests by referring the confidentiality, integrity and availability rate. Confidentiality refers to limiting the unauthorised tenant's green cloud data access using the additive homomorphic privacy property in proposed scheme. Additive homomorphic privacy property-based encryption function is developed to improve the privacy preserving level. To attain the integrity level between the tenant requests and green cloud server machine in GreenCloud-MTASHA3 scheme an encrypted trust data management process is carried out. Trustworthiness of tenant request is measured to maintain the consistency level on security with minimal computational time. The proposed scheme attains the confidentiality, integrity and availability rate on communicating task. Experiment is conducted on factors such as secure computation confidence, authorised tenant computational time and space taken on storing encrypted data.

Data prefetching and file synchronizing for performance optimization in Hadoop-based hybrid cloud

Driven by the technical factors such as system reliability, bandwidth constraints, data confidentiality and security, as well as the economic factors such as initial capital expenditure and re-occurring operating expenditure, today's cloud computing tends to adopt hybrid cloud model. However, because hybrid clouds scale both numerically and geographically, the network delay becomes the main constraint in remote file system access. To hide network latency and reduce job completion time in Hadoop-based hybrid cloud data access, a scheduling-aware data prefetching scheme to enhance non-local map task's data locality in Hadoop-based centralized hybrid cloud (CHCDLOS-Prefetch) and a file synchronizing method to decrease job execution delay in Hadoop-based distributed hybrid cloud (DHCDLO-Sync) are proposed. In the former, input data for non-local map tasks are fetched ahead of time to target compute nodes by making use of idle network bandwidth. In the latter, considered from job level scheduling, data files with high popularity are proactively synchronized beforehand among sub-clouds to strength intra sub-cloud data locality in distributed hybrid cloud. Extensive experimental results illustrate that compared to the Capacity, the Fair and the DARE algorithms, our proposed algorithms improve hybrid cloud performance more significantly in data locality and job completion time.

PriGuarder: A Privacy-Aware Access Control Approach Based on Attribute Fuzzy Grouping in Cloud Environments

Data privacy protection is crucial to cloud computing since privacy leakage may prevent users from using cloud services. To ensure data privacy, we propose PriGuarder , a novel privacy-aware access control method. This method spans the three stages of a cloud service, i.e., user registration, data creation, and data access. At each stage, users can choose two modes to interact with the cloud service provider, i.e., direct or indirect. With the indirect mode, an attribute fuzzy grouping scheme is introduced to ensure user identity privacy and attribute privacy in all the three stages. Furthermore, exploiting data encryption and timestamp techniques, new access control protocols are proposed to regulate interactions between users and the cloud service provider. We illustrate the use of our method in the context of Amazon S3. Theoretical analysis and comprehensive simulation experiments have been conducted, which demonstrate the efficacy of PriGuarder .

Secure Hash Algorithm based Multiple Tenant User Security over Green Cloud Environment

This paper proposes a green cloud multi-tenant trust authentication with secure hash algorithm-3 (GreenCloud-MTASHA3) scheme to eliminate the unauthorised tenant access. GreenCloud-MTASHA3 scheme provide security over the multiple tenant requests by referring the confidentiality, integrity and availability rate. Confidentiality refers to limiting the unauthorised tenant's green cloud data access using the additive homomorphic privacy property in proposed scheme. Additive homomorphic privacy property-based encryption function is developed to improve the privacy preserving level. To attain the integrity level between the tenant requests and green cloud server machine in GreenCloud-MTASHA3 scheme an encrypted trust data management process is carried out. Trustworthiness of tenant request is measured to maintain the consistency level on security with minimal computational time. The proposed scheme attains the confidentiality, integrity and availability rate on communicating task. Experiment is conducted on factors such as secure computation confidence, authorised tenant computational time and space taken on storing encrypted data.

Manage Cloud Data Access Control Anonymity with Attributed Based Encryption

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.

Control Cloud Data Access Privilge Anonymity with Attributed Based Encryption

Cloud computing is a revolutionary computing paradigm, which enables flexible, on-demand, and low-cost usage of computing resources, but the data is outsourced to some cloud servers, and various privacy concerns emerge from it. Various schemes based on the attribute-based encryption have been to secure the cloud storage. Data content privacy. A semi anonymous privilege control scheme AnonyControl to address not only the data privacy. But also the user identity privacy. AnonyControl decentralizes the central authority to limit the identity leakage and thus achieves semi anonymity. The Anonymity –F which fully prevent the identity leakage and achieve the full anonymity.

Efficient User Revocation Mechanism for Privilege and Anonymity in Control Cloud Data Access

The most engaging a part of the cloud computing is that the computation outsourcing, its far beyond enough to only conduct Associate in Nursing access management. Users need to regulate the privileges of knowledge manipulation over alternative users or cloud servers,this is often as a result of once sensitive data or calculation is outsourced to the cloud servers or another user, that is out of user’s management in most cases, privacy risks would raise dramatically as a result of the servers would possibly illicitly examine user’s knowledge and access sensitive data, or alternative users is also able to infer responsive information from the out-sourced calculation. Therefore, not alone the access but collectively the operation have to be compelled to be controlled.

CloudFile: A cloud data access control system based on mobile social trust

Personal data management at cloud with mobile devices confronts a number of practical challenges such as security, efficiency and usability. Many existing solutions suffer from high computation and communication costs, thus impractical to be deployed in mobile domains. Notably, high popularity of mobile social networking provides a good platform to assess social trust in a pervasive way, which can be applied to automatically manage personal data access at the cloud with sound performance and effectiveness. This paper presents the design and implementation of a personal cloud data access control system named CloudFile based on trust evaluation in mobile social networking. The CloudFile uses a Key Policy–Attribute Based Encryption (KP-ABE) scheme to control personal data access based on social trust in order to guarantee the safety of mobile cloud data storage. System performance tests show that the CloudFile is flexible for controlling data access, secure for personal data storage, and efficient to be deployed by mobile devices. Particularly, we investigate user acceptance on the CloudFile system. Based on user feedback, we conclude that the CloudFile is accepted with regard to perceived ease of use, practicality, user interface, playfulness and intuitive attitude.

User Behaviour Profiling in Cloud using One Class SVM: A Review

Distributed computing guarantees to on a very basic level change the way we utilize PCs and get to and store our own specific and business data. With these new registering and correspondences models develop new data security challenges. Existing information security structures, for instance, encryption have fizzled in imagining information theft strikes, particularly those executed by an insider to the cloud supplier. We propose a substitute methodology for securing information in the cloud utilizing adversarial mimic improvement. We screen data access in the cloud and perceive unpredictable data access outlines. Right when unapproved access is suspected and after that confirmed using test questions, we dispatch a disinformation strike by giving back a considerable measure of fake information to the attacker. This secures against the misuse of the customer's real data. Trials coordinated in a neighbor-hood archive setting give confirmation this technique may give unprecedented levels of customer data security in a Cloud space.