Efficient dynamic multi-replica auditing for the cloud with geographic location

Cloud computing that provides elastic computing and storage resource on demand has become increasingly important due to the emergence of “big data”. Cloud computing resources are a natural fit for processing big data streams as they allow big data application to run at a scale which is required for handling its complexities (data volume, variety and velocity). With the data no longer under users’ direct control, data security in cloud computing is becoming one of the most concerns in the adoption of cloud computing resources. In order to improve data reliability and availability, storing multiple replicas along with original datasets is a common strategy for cloud service providers. Public data auditing schemes allow users to verify their outsourced data storage without having to retrieve the whole dataset. However, existing data auditing techniques suffers from efficiency and security problems. First, for dynamic datasets with multiple replicas, the communication overhead for update verifications is very large, because each update requires updating of all replicas, where verification for each update requires O(log n ) communication complexity. Second, existing schemes cannot provide public auditing and authentication of block indices at the same time. Without authentication of block indices, the server can build a valid proof based on data blocks other than the blocks client requested to verify. In order to address these problems, in this paper, we present a novel public auditing scheme named MuR-DPA. The new scheme incorporated a novel authenticated data structure (ADS) based on the Merkle hash tree (MHT), which we call MR-MHT. To support full dynamic data updates and authentication of block indices, we included rank and level values in computation of MHT nodes. In contrast to existing schemes, level values of nodes in MR-MHT are assigned in a top-down order, and all replica blocks for each data block are organized into a same replica sub-tree. Such a configuration allows efficient verification of updates for multiple replicas. Compared to existing integrity verification and public auditing schemes, theoretical analysis and experimental results show that the proposed MuR-DPA scheme can not only incur much less communication overhead for both update verification and integrity verification of cloud datasets with multiple replicas, but also provide enhanced security against dishonest cloud service providers.

In cloud storage mode, users lose physical control over their data. To enhance the security of outsourced data, it is vital to audit the data integrity of the data owners. However, most of the current audit protocols have a single application scenario and cannot accommodate the actual needs of individuals and enterprises. In this research, a safe and efficient auditing scheme is proposed that is based on a hierarchical Merkle tree. On the one hand, we use a hierarchical authentication data structure and local signature aggregation technique to reduce the scale of the Merkle tree. In addition, authoritative nodes are introduced to reduce the length of the authentication path and improve the update efficiency. On the other hand, we introduce a monitoring mechanism that is based on the original data integrity auditing model to analyze the cloud data, which improves the transparency and credibility of cloud service providers. In addition, we achieve incomplete data recovery through log analysis, which greatly reduces the number of replicas of files under the premise of multi-copy auditing, reduces the burden on cloud service providers, and improves the fairness of audit protocols. The theoretical analysis and experimental comparison prove that the method is secure and efficient. It can effectively reduce the computational overhead and storage overhead in integrity auditing.

Cloud computing has emerged as a new computing paradigm, with provisioning model generally consisting of cloud service providers (CSPs), network service providers (NSPs), and end users. The associated economics has opened up a new research area; and with the expansion of the cloud computing market, the relationship between CSPs and NSPs, is changing profoundly. In addition to providing the default network services, traditional NSPs, in attempt to compete with CSPs, have started offering cloud services to end users. Though much progress has been made toward addressing competitions among CSPs themselves or among NSPs themselves, few studies have focused on the competition between CSPs and NSPs. In this paper, we investigate the problem of insufficient studies on the competition between CSPs and NSPs by presenting a new economic model to characterize the competition between CSPs and NSPs, and by conducting thorough theoretical analysis as well as numeric experiments to validate the proposed model. We believe, based on results, that the proposed economic model is general and feasible, and thus is applicable to modeling the competition among service providers in cloud computing market.

Increasingly more and more organizations are opting for outsourcing data to remote cloud service providers (CSPs). Customers can rent the CSPs storage infrastructure to store and retrieve almost unlimited amount of data by paying fees metered in gigabyte/month. For an increased level of scalability, availability, and durability, some customers may want their data to be replicated on multiple servers across multiple data centers. The more copies the CSP is asked to store, the more fees the customers are charged. Therefore, customers need to have a strong guarantee that the CSP is storing all data copies that are agreed upon in the service contract, and all these copies are consistent with the most recent modifications issued by the customers. In this paper, we propose a map-based provable multicopy dynamic data possession (MB-PMDDP) scheme that has the following features: 1) it provides an evidence to the customers that the CSP is not cheating by storing fewer copies; 2) it supports outsourcing of dynamic data, i.e., it supports block-level operations, such as block modification, insertion, deletion, and append; and 3) it allows authorized users to seamlessly access the file copies stored by the CSP. We give a comparative analysis of the proposed MB-PMDDP scheme with a reference model obtained by extending existing provable possession of dynamic single-copy schemes. The theoretical analysis is validated through experimental results on a commercial cloud platform. In addition, we show the security against colluding servers, and discuss how to identify corrupted copies by slightly modifying the proposed scheme.

Efficient integrity verification of replicated data in cloud computing system

An important problem in Cloud computing is data backup and disaster recovery in the event of network or cloud service provider failure. Most cloud service providers offer data backup at their premises at premium cost which might not be affordable by consumers and SMB's. Here we introduce a simple solution for this complex problem in the form of a mechanism for online data backup for cloud along with disaster recovery. This approach reduces the cost of the solution and not only protects data from disaster but also makes the process of migration from one cloud service provider to another, much simpler. This solution eliminates consumers' dependency on the service provider and also eliminates the associated data backup cost. A simple hardware box can do all these at little cost.

Cloud federation is introduced to eliminate the resource limitation problem of individual Cloud Service Provider (CSP). In a federation, one CSP can outsource their overhead requests by hiring unused resources from other CSPs in the federation and CSPs cash greater revenue. In this paper, we propose a system that maximizes this revenue while putting some factor constraints in satisfactory standard. Factors include response time of instances that is analogous to Quality of Service (QoS), and profit that maintains a certain reputation. Response time is reduced by considering geographical location of the user and the data center of desired resources. In this system, CSPs choose suitable resources from resource pool of cloud federation that maximizes the profit while preserving Quality of Service (QoS) high and minimizing the rejection rate of user requests. We map factor constraints to MMKP (Multi-choice Multidimensional Knapsack Problem) algorithm and define objective function for revenue maximization. We calculate response time by Cloud Analyst to measure the QoS. Experimental results show that the proposed system can effectively increases QoS level by reducing response time and rejection requests in a cloud federation that eventually increases the revenue of the CSP.

This work analyzes the probability of collisions in Merkle graphs, with a focus on a specific class of attacks in balanced Merkle trees. To provide a tractable model, each hash function is modeled as an independent random oracle with finite input space. We provided a general methodology for computing collision probabilities in arbitrary Merkle graphs, when an arbitrary amount of leaves is modified. The main finding of this study is the fact that an attack carried out modifying multiple leaves is not necessarily more powerful than the one carried out modifying only one leaf. Specifically, the collision probability depends on the height of the attacked Merkle tree, increasing for higher trees, and on the position of the modified nodes in the tree.

A blockchain-based dynamic and traceable data integrity verification scheme for smart homes

In this research manuscript, a new protocol is proposed for predicting the available space in the cloud and verifying the security of stored data. The protocol is utilized for learning the available data, and based on this learning, the available storage space is identified, after which the cloud service providers allow for data storage. The Integrity verification separates the private and the public data, which avoids privacy issues. The integration of the private data is done with the help of cloud service providers with respect to the third-party auditing (TPA). Earlier, public key cryptography and bilinear map technologies have been combined by the researchers, but the computation time and costs were high. To secure the integrity of the data storage, the client should execute several computations. Therefore, this research suggests a reliable and effective method called position-aware Merkle tree (PMT), which is implemented for ensuring data integrity. The proposed system uses a PMT that enables the TPA to perform multiple auditing tasks with high efficiency, less computational cost and computation time. Simulation results clearly shows that the developed PMT method consumed 0.00459 milliseconds of computation time, which is limited when compared to the existing models.

The operational cost minimization in distributed clouds via community-aware user data placements of social networks

Using cloud data clients may transfer data from their computer systems to cloud servers. Hence, user will not have any burden of maintenance and also he gets high quality data storage services. Many security issues are concerned with cloud storage. Cloud service providers or storage servers are not completely trustworthy. The user is concerned about the information stored on cloud are in place or not turns. This paper is based on homomorphic hash algorithm. Further this supports dynamic operations such as insert, update, delete and modify at block level, for data dynamics Merkle Hash Tree is used which helps to find the location of each dynamic operation. Third party auditor checks the user's data for correctness and gives the accuracy of the data that is stored in cloud server. The communication and computation overhead are reduced. Deduplication technique is used to check whether the file that user need to store in cloud storage is already exist at cloud server or not. This framework is effective and secure against replace attack launch by malicious server.

The Data Integrity Based Secure Cloud Data Outsourcing Model involves designing a framework that ensures data outsourced to the cloud remains secure, intact, and authentic. Cloud computing has become an indispensable resource for businesses and individuals alike, providing scalable and cost-effective solutions for data storage and management. However, outsourcing data to external cloud service providers (CSPs) raises serious questions around data security, integrity, and authenticity. It is essential to retain confidence and comply with regulatory criteria to make sure that outsourced data is authentic, obtainable, and unaltered. In this article, the Low-Complexity Elliptic Galois Cryptography based Secure Data Integrity Verification Scheme for Cloud Storage (LCEGC-SDIV-CS) is proposed. Initially, the integration of the advantages in Trusted Execution Environment (TEE) and identity-based encryption using Low-Complexity Elliptic Galois Cryptography (LCEGC) is provided to create a safe data integrity verification scheme. Then, data integrity using Block Access Signature Oriented Merle Hash Tree (BS-MHT) is used for the integrity-preserving structure for encrypted block-oriented storage systems. The random Oracle model's security analysis, depending upon the computational Diffie-Hellman assumption, provides security by preventing attacks when the adversary chooses the messages with targets’ identities. The proposed LCEGC-SDIV-CS model is implemented and the performance metrics like Data uploading with downloading time, Memory usage on data uploading with downloading, Encryption time, Decryption time, and Security levels are examined. The proposed LCEGC-SDIV-CS method attains 21.56%, 23.98%, and 21.19% lower data uploading with downloading time 24.78%, 23.82%, and 23.52% lower encryption time are analyzed with existing methods EDI-SPD-SCS, NSA-SADS-BDEPDP-SDS-RCS respectively.

In order to keep the confidential data in the cloud against unauthorized parties, a cryptographic access control solution based on Attribute-Based Encryption (ABE) and Identity-Based Signature (IBS) is introduced in this paper. Under the premise that cloud service provider is untrustful, the proposed scheme can ensure the data security of the cloud storage system in an open environment, as well as reduce the complexity of management. Analysis and experimental results show that the scheme can be semantically secure against adaptive chosen ciphertext attacks under the random oracle model. Our concrete access control scheme can enhance the efficiency of the cloud to a certain extent.

Mobile cloud computing blend mobile and cloud computing together with the help of wireless communication technology to achieve benefits for the stakeholders. These stakeholders include mobile users, mobile service operators and cloud service providers. Assorted challenges are also there for the implementation of mobile cloud computing but security and privacy are the dominant concerns. In order to achieve security and privacy of the said system several attempts are taken up. As the underlying system is complex and more prone against security threats, therefore strong authentication and privacy preserving schemes are desired. Three factor biometrics based authentication schemes are considered more secure for such huge and complex systems. Moreover, computational intelligence is getting popular nowadays for designing more vigorous and reliable biometrics based authentication schemes. Very recently, Tsai and Lo proposed an identity based authentication scheme for distributed mobile cloud computing environments. They claimed to achieve single sign on authentication for multiple service providers. Furthermore, they emphasized the usefulness and security of their scheme. However, the analysis in this paper shows that Tsai and Lo’s scheme is insecure against server forgery attack. It is proved that any adversaries having knowledge of just public parameters can forge as a valid service provider. Then an improved scheme is proposed to mitigate the security weakness. The security of proposed scheme is instantiated under random oracle model as well as the protocol validation model of popular automated tool ProVerif.