Multiple Cloud Users Research Articles

KBD-Share: Key Aggregation, Blockchain, and Differential Privacy based Secured Data Sharing for Multi-User Cloud Computing

In today's era of widespread cloud computing and data sharing, the demand for secure and privacy-preserving techniques to facilitate multi-user data sharing is rapidly increasing. However, traditional approaches struggle to effectively address the twin objectives of ensuring privacy protection while preserving the utility of shared data. This predicament holds immense significance due to the pivotal role data sharing plays in diverse domains and applications. However, it also brings about significant privacy vulnerabilities. Consequently, innovative approaches are imperative to achieve a harmonious equilibrium between the utility of shared data and the protection of privacy in scenarios involving multiple users. This paper presents KBD-Share, an innovative framework that addresses the intricacies of ensuring data security and privacy in the context of sharing data among multiple users in cloud computing environments. By seamlessly integrating key aggregation, blockchain technology, and differential privacy techniques, KBD-Share offers an efficient and robust solution to protect sensitive data while facilitating seamless sharing and utilization. Extensive experimental evaluations convincingly establish the superiority of KBD-Share in aspects of data privacy preservation and utility, outperforming existing approaches. This approach achieves the highest R2 value of 0.9969 exhibiting best data utility, essential for multi-user data sharing in diverse cloud computing applications.

A truthful dynamic combinatorial double auction model for cloud resource allocation

Dynamic auction-based resource allocation models require little global price information, are decentralized and suitable for the distributed systems like cloud computing. For the cloud computing market, we proposed a Truthful Dynamic Combinatorial Double Auction (TDCDA) model to improve the social welfare and resource utilization. In our model, multiple cloud service providers and cloud users bid for various resources in a dynamic environment. We adopted a payment scheme to ensure truthfulness for all participants, which motivates bidders to reveal their true preferences. Since the combinatorial auction allocation with goal of economic efficiency is NP-hard, we developed a greedy mechanism to achieve the approximately efficient solution. Considering both parties’ interests and the resource scarcity, this model also ensures fairness and balances resource allocation. The proposed model is proven to be approximately efficient, incentive compatible, individually rational and budget-balanced. Simulation results show that the model not only achieves economic efficiency, but also improves resource allocation and meets resource needs for more cloud users.

Cloud vendor selection for the healthcare industry using a big data-driven decision model with probabilistic linguistic information.

The role of cloud services in the data-intensive industry is indispensable. Cision recently reported that the cloud market would grow to 55 billion USD, with an active contribution of the cloud to healthcare around 2025. Inspired by the report, cloud vendors expand their market and the quality of services to seek growth globally. The rapid growth of the cloud sector in the healthcare industry imposes a challenge: making a rational choice of a cloud vendor (CV) out of a diverse set of vendors. Typically, the healthcare industry 4.0 sees the issue as a large-scale group decision-making problem. Previous studies on a CV selection face certain challenges, such as (i) a lack of the ability to handle multiple users’ views, as well as experts’/users’ complex linguistic views; (ii) the confidence level associated with a view is not considered; (iii) the transformation of multiple users’ views into holistic data is lacking; and (iv) the systematic prioritization of CVs with minimum human intervention is a crucial task. Motivated by these challenges and circumventing them, a new big data-driven decision model is put forward in this paper. Initially, the data in the form of complex expressions are collected from multiple cloud users and are further transformed into a holistic decision matrix by adopting probabilistic linguistic information (PLI). PLI represents complex linguistic expressions along with the associated confidence levels. Later, a holistic decision matrix is formed with the missing values imputed by proposing an imputation algorithm. Furthermore, the criteria weights are determined by using a newly proposed mathematical model and partial information. Finally, the evaluation based on the distance from average solution (EDAS) approach is extended to PLI for the rational ranking of CVs. A real-time example of a CV selection for a healthcare center in India is exemplified so as to demonstrate the usefulness of the model, and the comparison reveals the merits and limitations of the model.

Data Storage Security in the Cloud Environment Using the Honey Pot System

Cloud computing is a framework for delivering services through a shared network. It should follow certain procedures or mechanisms to protect and make the cloud data more reliable. In secure cloud computing, the implementation and service delivery model are dealt with. Cloud security could be viewed as a provider and customer responsibility depending on their design and level. There are cases where multiple cloud users can use the same information to create service abnormalities, which is called ‘multitenancy.' In a multi-tenant model, the resources are isolated between different users and it is done by segmentation to achieve the goal of data security between many users. In the user access area, user access to common resources is also limited. The software is aware of the actions of the client and acts accordingly if unauthorized access is detected. The authors propose a clear idea of the data storage security of cloud information through honeypot in cloud monitoring applications and various cloud security scheme key models used and also identifies the audit time and invalid response time.

Privacy-Preserving Association Rule Mining Using Homomorphic Encryption in a Multikey Environment

With the development of big data and cloud computing, data analysis technologies play an important role to produce huge market values. Customers with limited computing resources may resort to the cloud to perform some association rule mining tasks. Data owners may have a risk of personal sensitive information leakage in this process. To preserve privacy in outsourced data, data owners may encrypt raw data before uploading. Data analysis of encrypted data is a challenge that has attracted the attention of many researchers in recent years. Homomorphic encryption is a cryptographic tool, which is one of the ways to solve this challenge. It allows data processing of encrypted data without decryption. Researching homomorphic encryption schemes that support privacy-preserving data mining in a multikey environment has become a significant direction. In this article, we propose a novel homomorphic cryptosystem, which supports multiple cloud users to have different public keys. Besides, we propose a privacy-preserving association rule mining scheme on outsourced data uploaded from multiple parties in a twin-cloud architecture. Our scheme uses a transaction record representation method in databases for large shopping malls based on real-world situations, and our experiments on a real transaction database show that our technology is reasonably feasible.

A Novel Approach for Dynamic Apportion and De-Allocate Resources from the Cloud

Cloud computing is on demand as it offers dynamic flexible resource allocation for reliable and guaranteed services in pay as-you-use manner to public. In Cloud computing multiple cloud users can request number of cloud services simultaneously. So there must be a provision that all resources are made available to requesting user in efficient manner to satisfy their need. Hence there is no need for getting licenses for individual products. Virtual Machine (VM) technology has been employed for resource provisioning. It is expected that using virtualized environment will reduce the average job response time as well as executes the task according to the availability of resources. Effective and dynamic utilization of the resources in cloud can help to balance the load and avoid situations like slow run of systems.

Improved secure fuzzy auditing protocol for cloud data storage

Nowadays, more and more people prefer to outsource their storage to the cloud; however, due to some accidents, cloud storage service providers may lose some data outsourced by the data owners. Thus a mechanism to ensure the outsourced cloud data remaining intact is needed for smoothly running the cloud storage service. Fuzzy cloud auditing protocol is such a mechanism running between data owners and cloud storage service providers. In these protocols, the data owner fuzzy challenges the cloud storage servers on the randomly chosen data blocks with random values, the servers need to response with corrected aggregated tag proof to pass through the auditing process. Until now, there are many fuzzy cloud auditing protocols with various interesting properties. In 2015, Yuan et al. proposed an auditing scheme supporting publicly integrity checking and dynamic data sharing with multi-user modification, which aims at allowing multiple cloud users to modify data while ensuring the cloud data’s integrity. Also recently Yuan et al. proposed a public proofs of retrievability (POR) in cloud with constant cost, they showed their scheme is the first POR scheme which can simultaneously achieve public verifiability, constant communication and computational costs on users, and prove the security of their scheme. However, in this paper, we show their schemes are not secure, concretely, the tags in their schemes can be easily forged. We also give an improved fuzzy cloud auditing scheme for the data owners.

Comparable encryption scheme supporting multiple users in cloud computing

Comparable encryption scheme supporting multiple users in cloud computing

A Literature Survey: Resource Management Mechanism in Cloud Environment

Today, Cloud Computing is considered as one of the rising field of researchers. It turns out to be a quite prominent between different types of cloud users. It compromises with on demand resource since it offers reliable and assured services to the customer. Resource allocation for cloud computing is a proving work and procedure of allocating the resources to cloud relies on upon the QoS prerequisites of cloud environment. Resources are not accessible as indicated by QoS prerequisite then the Workload Management System makes a request to retransmitting the workload with new QoS necessities as SLA. In the Cloud computing world, multiple numerous cloud users could be requested number of cloud services in parallel. So there must be an arrangement that all resources which are made accessible to asking for a client in a productive way to fulfil their needs. Resource allocation is performed by the target of diminishing the costs related with it. The tasks of resource allocation are taking care of client requests and application necessities. In this paper, present a review of diverse resource allocation techniques that have been in view of the distinctive parameters and there is findings as well as discussion about the issues or challenges of cloud computing environment has been discussed. A mathematical analysis with the help of Hungarian method is also discussed Keywords: Cloud; Resource allocation; QoS; SLA; virtual machine.

Efficient Integrity Verification Scheme for Medical Data Records in Cloud-Assisted Wireless Medical Sensor Networks

Wireless sensor networks (WSNs) have been widely used in many applications recently. As an important application of the WSNs, the wireless medical sensor networks (WMSNs) could improve health-care quality and have become significant in the modern medical system. WMSNs devices typically have limited computing, storage and communication capabilities. To enhance the capabilities of WSNs, cloud-assisted WMSNs have been introduced, and they can provide more efficient processing of cloud users’ medical data records stored in the cloud. The integrity of medical data records is very important since these data will be used to provide a medical diagnosis and other medical treatments. In this paper, we propose an efficient integrity verification scheme for medical data records in cloud-assisted WMSNs. Based on elliptic curve digital signature algorithm, we construct linearly homomorphic authenticator, so that the third party auditor (TPA) can verify the the integrity of medical data records without bringing in new security threats. TPA does not need to retrieve the entire medical data records, thus can dramatically reduce the communication and computation overhead. Moreover, we further extend our scheme to support batch integrity verification for multiple cloud users simultaneously. In particular, to achieve efficient medical data dynamic operations, using index hash tables, our scheme can execute dynamic operations efficiently. Performance comparison shows that our scheme is more light-weight, and can be used much more practically in cloud-assisted WMSNs.

OGPADSM<SUP align="right">2</SUP>: oriented-group public auditing for data sharing with multi-user modification

In most data sharing protocols for cloud storage, to update the outsourced data, the data updating operation is only executed by data owner. Obviously, it is far from practical owing to the tremendous computational cost on data owner. Until now, there are a few protocols in which multiple cloud users are allowed to update the outsourced data with integrity assurance. And these protocols do not consider collusion attack between misbehaving cloud servers and the revoked users, which is an important challenge in data sharing protocol. To support multi-user modification and resist collusion attack, we propose a novel public auditing for data sharing with multi-user modification in this paper. Our scheme does not support public checking and efficient user revocation, but provides backward security. At the same time, our scheme is provably secure under the bilinear Diffie-Hellman problem. To increase efficiency of the auditor's verification, an improved protocol is given. In the improved protocol, only one pairing operation is required in the auditor's verification phase. By comparison with the other protocols, our scheme has lower computation cost on the auditor and stronger security.

Efficient public auditing for data migration across cloud systems

Cloud storage has gained great attention in recent years. It brings many benefits as well as security issues. Cloud auditing technology can ensure the integrity of cloud users' data. However, it lacks efficiency when dealing with the migration scenario of a large amount of cloud data. In this paper, we propose an efficient cloud auditing scheme which supports data migration auditing. We first construct a privacy-preserving auditing scheme that can audit cloud data during data migration, which can hugely reduce the migration cost when data corruption happens. We further extend the scheme to support data update during auditing. By supporting batch auditing for multiple cloud users' migration auditing tasks, our scheme could hugely improve the efficiency. Performance analysis demonstrates that our auditing scheme is secure and efficient.

A Framework of Price Bidding Configurations for Resource Usage in Cloud Computing

In this paper, we focus on price bidding strategies of multiple users competition for resource usage in cloud computing. We consider the problem from a game theoretic perspective and formulate it into a non-cooperative game among the multiple cloud users, in which each cloud user is informed with incomplete information of other users. For each user, we design a utility function which combines the net profit with time efficiency and try to maximize its value. We design a mechanism for the multiple users to evaluate their utilities and decide whether to use the cloud service. Furthermore, we propose a framework for each cloud user to compute an appropriate bidding price. At the beginning, by relaxing the condition that the allocated number of servers can be fractional, we prove the existence of Nash equilibrium solution set for the formulated game. Then, we propose an iterative algorithm ( <inline-formula> <tex-math notation="LaTeX">$\mathcal {IA}$</tex-math></inline-formula> ), which is designed to compute a Nash equilibrium solution. The convergency of the proposed algorithm is also analyzed and we find that it converges to a Nash equilibrium if several conditions are satisfied. Finally, we revise the obtained solution and propose a near-equilibrium price bidding algorithm ( <inline-formula><tex-math notation="LaTeX">$\mathcal {NPBA}$</tex-math></inline-formula> ) to characterize the whole process of our proposed framework. The experimental results show that the obtained near-equilibrium solution is close to the equilibrium one.

Strategy Configurations of Multiple Users Competition for Cloud Service Reservation

In this paper, we focus on strategy configurations of multiple users to make cloud service reservation. We consider the problem from a game theoretic perspective and formulate it into a non-cooperative game among the multiple cloud users, in which each user is informed with incomplete information of other users. For each user, we design a utility function which combines the net profit with time efficiency and try to maximize its value. We solve the problem by employing variational inequality (VI) theory and prove that there exists a Nash equilibrium solution set for the formulated game. Then, we propose an iterative proximal algorithm (IPA), which is designed to compute a Nash equilibrium solution. The convergence of the IPA algorithm is also analyzed and we find that it converges to a Nash equilibrium if several conditions are satisfied. Finally, we conduct some numerical calculations to verify our theoretical analysis. The experimental results show that our proposed IPA algorithm converges to a stable state very quickly and improves the utilities of all users to certain extent by configuring a proper request strategy.

Comparable encryption scheme supporting multiple users in cloud computing

Cloud computing provides a way for secure data sharing, where data should be converted into ciphertext forms before uploading to the cloud servers. At the same time, we need to compare the data on many occasions. Although the privacy is enhanced when data is encrypted, the comparison of encrypted data is inconvenient, especially the data encrypted by different keys. The techniques for secure comparison of ciphertexts are a hot research topic both in the academic research and the industry practice. However, to the best of our knowledge, only a single user's data encrypted by a single key can be compared in the existing schemes. In this paper, we design the first comparable encryption scheme among multiple users, and a novel token transformation technique is provided. In our scheme, different ciphertexts encrypted by different keys can be compared with each other by using our new algorithm and token transformation method. In addition, the security and verifiability characteristics of our scheme guarantee that users can easily verify the comparison result, and the value of the data will not be revealed. Finally, our scheme is flexible, which can be widely used in cloud computing.

Public Integrity Auditing for Dynamic Data Sharing With Multiuser Modification

In past years, the rapid development of cloud storage services makes it easier than ever for cloud users to share data with each other. To ensure users' confidence of the integrity of their shared data on cloud, a number of techniques have been proposed for data integrity auditing with focuses on various practical features, e.g., the support of dynamic data, public integrity auditing, low communication/computational audit cost, and low storage overhead. However, most of these techniques consider that only the original data owner can modify the shared data, which limits these techniques to client read-only applications. Recently, a few attempts started considering more realistic scenarios by allowing multiple cloud users to modify data with integrity assurance. Nevertheless, these attempts are still far from practical due to the tremendous computational cost on cloud users, especially when high error detection probability is required by the system. In this paper, we propose a novel integrity auditing scheme for cloud data sharing services characterized by multiuser modification, public auditing, high error detection probability, efficient user revocation as well as practical computational/communication auditing performance. Our scheme can resist user impersonation attack, which is not considered in existing techniques that support multiuser modification. Batch auditing of multiple tasks is also efficiently supported in our scheme. Extensive experiments on Amazon EC2 cloud and different client devices (contemporary and mobile devices) show that our design allows the client to audit the integrity of a shared file with a constant computational cost of 340 ms on PC (4.6 s on mobile device) and a bounded communication cost of 77 kB for 99% error detection probability with data corruption rate of 1%.

Privacy Preserving using Data Partitioning Technique for Secure Cloud Storage

Computing is a utility computing such asPay-as-you-go computing, Illusion of Infinite Resources, No UpfrontCost, Fine grained billing. User's store their large amountof data on a cloud severs at remote place without worryingabout Storage Correctness as well as information Integrity. Sothat users can option to a Third Party Auditor (TPA) to testthe data integrity and be worry-free because user does not physical present at all time. The Third Party Auditor(TPA) performs audits for multiple cloud users simultaneouslyand efficiently.In this paper, proposed scheme contain data files dividedinto small block technique. which ensure cloud storage security, integrity. To increase the user level security we proposed One Time Password (OTP) at the time of file uploading. Partitioning process implemented at TPA side. TPA performs operation like data files divided into small part of block, take hash of each block, each block Encrypt using cryptographic algorithm.

On Developing Fair and Orderly Cloud Markets

While cloud markets promise virtually unlimited resource supplies, standardized commodities and proper services, some providers may not be able to offer effectual physical capacity to serve large customers. A solution is cloud collaborations, in which multiple providers unite forces in order to conjointly offer capacities in the cloud markets. Supposably, both the Quality of Service and security properties of such collaborations will be determined by “the weakest link in the chain”, therefore resulting in a trade-off between the monetary aggregates, cumulative capacity and the non-functional attributes of a cloud collaboration. Based on previous research, this paper examines efficient composition of cloud collaborations from the broker's perspective, considering Quality of Service and information security requirements of multiple cloud providers and users and presents an exact approach CCCP-EXA.KOM for building cloud collaborations. Furthermore, it proposes a Mixed Integer Programming-based heuristic optimization approach CCCP-PRIOSORT.KOM and provides its quantitative evaluation in comparison with prior optimal approach.

Enhanced Monitoring-as-a-Service for Effective Cloud Management

This paper introduces the concept of monitoring-as-a-service (MaaS), its main components, and a suite of key functional requirements of MaaS in cloud. We argue that MaaS should support not only the conventional state monitoring capabilities, such as instantaneous violation detection, periodical state monitoring, and single tenant monitoring, but also performance-enhanced functionalities that can optimize on monitoring cost, scalability, and the effectiveness of monitoring service consolidation and isolation. In this paper, we present three enhanced MaaS capabilities and show that window-based state monitoring is not only more resilient to noises and outliers, but also saves considerable communication cost. Similarly, violation-likelihood-based state monitoring can dynamically adjust monitoring intensity based on the likelihood of detecting important events, leading to significant gain in monitoring service consolidation. Finally, multitenancy support in state monitoring allows multiple cloud users to enjoy MaaS with improved performance and efficiency at more affordable cost. We perform extensive experiments in an emulated cloud environment with real-world system and network traces. The experimental results suggest that our MaaS framework achieves significant lower monitoring cost, higher scalability, and better multitenancy performance.

A SURVEY ON VARIOUS RESOURCE ALLOCATION POLICIES IN CLOUD COMPUTING ENVIRONMENT

Cloud computing is bringing a revolution in computing environment replacing traditional software installations, licensing issues into complete on-demand services through internet. In Cloud computing multiple cloud users can request number of cloud services simultaneously. So there must be a provision that all resources are made available to requesting user in efficient manner to satisfy their need. Resource allocation is based on quality of service and service level agreement. In cloud computing environment, to allocate resources to the user there are several methods but provider should consider the efficient way to guarantee that the applications’ requirements are attended to correctly and satisfy the user’s need This paper survey different resource allocation policies used in cloud computing environment.