Auditing a Cloud Provider’s Compliance With Data Backup Requirements: A Game Theoretical Analysis

Ismail, Ziad; Kiennert, Christophe; Leneutre, Jean; Chen, Lin

doi:10.1109/tifs.2016.2549002

Cited by 28 publications

(12 citation statements)

References 16 publications

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“…When direct reputation evaluation cannot reach a conclusion, X will implement a reliable recommendation reputation evaluation model based on dynamic game theory strategy [25].…”

Section: Establishing Model Evaluation Systemmentioning

confidence: 99%

A Security Reputation Model for IoT Health Data Using S-AlexNet and Dynamic Game Theory in Cloud Computing Environment

et al. 2019

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With the rapid development of cloud computing, users are exposed to increasingly serious security threats such as data leakage and privacy exposure when using cloud platform services. Problems in data security, such as inaccurate screening of indicators, lack of scientific validation of reputation evaluation results are also existed. In order to solve the problems, based on cloud environment, a security reputation model using S-AlexNet convolutional neural network and dynamic game theory (SCNN-DGT) is proposed. And it is used to protect the privacy of health data in Internet of Things (IoT). Firstly, the text information of user health data is pre-classified by using S-AlexNet convolutional neural network. Then, a recommendation incentive strategy based on dynamic game theory is proposed. So that the reputation model of user health data security is built, and the evaluation system of the model is established. Finally, an experimental study is carried out to verify the validity of the model and the model index screening. It is shown by experimental results that the model can solve the problems of low reliability of health data screening index, and low accuracy of credit distinction in cloud environment. Therefore, the reliability of mobile terminals is improved, and data security and privacy protection of mobile cloud services are strengthened effectively. INDEX TERMS Health data privacy protection, cloud computing, S-AlexNet convolutional neural network, dynamic game theory, big data security reputation model, recommendation incentive strategy, Internet of Things (IoT).

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“…When direct reputation evaluation cannot reach a conclusion, X will implement a reliable recommendation reputation evaluation model based on dynamic game theory strategy [25].…”

Section: Establishing Model Evaluation Systemmentioning

confidence: 99%

A Security Reputation Model for IoT Health Data Using S-AlexNet and Dynamic Game Theory in Cloud Computing Environment

et al. 2019

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“…The storage space of version data is boosted with the increase of the version files. At the same time, the opportunity of any corrupted version file being identified is decreased since the existing verification algorithms are only oriented to every file instead of a set of version files [10,11] while these files are randomly extracted. A large number of version files result in more verification cost.…”

Section: Motivationmentioning

confidence: 99%

“…This scheme is also applicable to multiple users and multiple clouds. Ziad et al [11] proposed a scheme based on game theory in order to find an optimal data verification strategy. Recently, Zhang et al [15] used indistinguishability obfuscation to reduce the auditor's computation overhead while the auditor is equipped with a low-power device.…”

Section: Related Workmentioning

confidence: 99%

“…(2) Attacker reduces the number of copies of the same data to save the storage space so that any part in a series of version files being corrupted will be unable to guarantee the integrity of version files. Generally, three copies of the same data are stored to maintain data service availability since the availability of users' data depends heavily on the number of copies [11]. The unreasonable storage model of version files further increases the potential risk of data corruption.…”

Section: Attack Modelmentioning

confidence: 99%

“…These misgivings have prompted the data owners to worry whether the outsourced data are intact or corrupted on the remote servers since they are deprived of the direct control of these data [2]. Data integrity verification [2][3][4][5][6][7][8][9][10][11][12] has been proposed to check the integrity of owners' remote stored data. These existing verification algorithms based on homomorphism technology can exactly identify the corrupted data (i.e., each block or file) in the verification.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A generic integrity verification algorithm of version files for cloud deduplication data storage

Lai

et al. 2018

EURASIP J. on Info. Security

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Data owners' outsourced data on cloud data storage servers by the deduplication technique can reduce not only their own storage cost but also cloud's. This paradigm also introduces new security issues such as the potential threat of data lost or corrupted. Data integrity verification is utilized to safeguard these data integrity. However, the cloud deduplication storage only focuses on file/chunk level to store one copy of the same data hosted by different data owners, and is not concerned with the same part of different data, e.g., a series of version files. We propose an integrity verification algorithm of different version files. The algorithm establishes the generic storage model of different version control methods to improve the universality of data verification. Then, the methods of verification tags and proofs generating are improved based on the index pointers corresponding to the storage relationship in the version groups and chained keys. Finally, the random diffusion extraction based on the random data sampling in the version group is proposed to improve the verification efficiency. The results of theoretical and experimental analysis indicate that the algorithm can achieve fast and large-scale verification for different version data.

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A game theoretic method to model and analyze attack‐defense strategy of resource service in cloud application

Fan

Chen

2017

Concurrency and Computation

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Cloud computing has attracted much attention recently in both industry field and academic research area. More and more Internet applications are moving to the cloud environment. However, it is difficult to construct perfectly secure mechanisms facing up with complex and various attacks in cloud computing, the efficient attack-defense strategy is highly demanded. In this paper, a stochastic game model is proposed based on combining stochastic Petri nets with game theory, which is used to describe the attack-defense behaviors in cloud computing. The physical machine, attack-defense behavior, and their attributes are also modeled by stochastic game model thus forming the attack-defense game model of cloud computing. On this basis, the Nash equilibrium of attack-defense process in physical machine is computed to get the optimal defense strategy. The related theories of Petri nets and the reachable states of attack-defense game model are used to formally verify the correctness and effectiveness of the proposed method. The enforcement algorithm is proposed to make cloud computing dynamically evaluate and select the defense strategy to against attack behavior as quickly as possible. Both case study and simulation results show that the proposed method can adapt quickly to the changes in cloud application thus improving the security of cloud computing.

show abstract

Auditing a Cloud Provider’s Compliance With Data Backup Requirements: A Game Theoretical Analysis

Cited by 28 publications

References 16 publications

A Security Reputation Model for IoT Health Data Using S-AlexNet and Dynamic Game Theory in Cloud Computing Environment

A Security Reputation Model for IoT Health Data Using S-AlexNet and Dynamic Game Theory in Cloud Computing Environment

A generic integrity verification algorithm of version files for cloud deduplication data storage

A game theoretic method to model and analyze attack‐defense strategy of resource service in cloud application

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