Query optimization mechanisms in the cloud environments: A systematic study

Azhir, Elham; Navimipour, Nima Jafari; Hosseinzadeh, Mehdi; Sharifi, Arash; Darwesh, Aso Mohammad

doi:10.1002/dac.3940

Cited by 24 publications

(15 citation statements)

References 88 publications

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“…2) CheckLog. U checks the validity of the auditing results as follows: a) acquire t (1) , t (1) + ϕ + 1, derive the actual time when the audit was performed from t (1) and t (1) + ϕ + 1, and reject if the time does not match the agreed one; b) extract t1 from the blockchain, and reject if the extraction fails; c) check whether t1 matches the entry in the first row of f , and rejects if t1 does not match the agreed one; d) compute τ = H(name n r 1 P K U ), i…”

Section: And Providementioning

confidence: 99%

“…Massive data at local storage cause a series of difficulty in management. To reduce heavy burden of data storage and maintenance in local storage, many users choose to outsource their data into cloud [1]. As an excellent tool, cloud brings tremendous benefits and convenience to our life.…”

Section: Introductionmentioning

confidence: 99%

“…According to [7], the most critical threats of cloud storage is data integrity and privacy leakage. In recent years, a series of cloud storage security incidents have drawn highly attention of the public 1 . Take Under Armour data breach as an example.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Decentralized and Privacy-Preserving Public Auditing for Cloud Storage Based on Blockchain

Miao¹,

Huang²,

Xiao³

et al. 2020

IEEE Access

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Cloud storage systems provide a flexible, convenient and friendly way for users to outsource data. However, users lose control of their data once outsourcing them to the cloud. Public auditing was introduced to ensure data integrity, in which a third-party auditor (TPA) is delegated to execute auditing tasks. In general, TPA generates and sends challenge information to the cloud server (CS), which proves data possession accordingly. However, the TPA may not perform public auditing protocol honestly or may even collude with CS to deceive users. Some existing public auditing schemes utilize blockchain to resist against the malicious TPA. However, the CS may guess the challenge messages and there is a risk that users' information may be leaked to the TPA during the process of auditing. In this paper, we propose a decentralized and privacy-preserving public auditing scheme based on blockchain (DBPA), in which a blockchain is utilized as an unpredictable source for the generation of (random) challenge information, and the auditor is required to record the audit process onto the blockchain. Due to the characteristics of blockchain, users can check the audit results publicly. Moreover, zero-knowledge proof is used in DBPA to protect user's privacy during the audit process so that the response information returned by the CS does not leak information about user's data. Security analysis and performance evaluation show that DBPA is secure and efficient.

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Section: And Providementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Decentralized and Privacy-Preserving Public Auditing for Cloud Storage Based on Blockchain

Miao¹,

Huang²,

Xiao³

et al. 2020

IEEE Access

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show abstract

“…This query is also taking more space during this data process [18]. To avoid this problem query optimization is also needed [19]. Energy consuming, necessary memories, operating time, essential storage are some of the perspectives that have to be considered during the optimization process [20].…”

Section: Problem Statementmentioning

confidence: 99%

Securing Cloud Data Against Cyber-Attacks Using Hybrid Aes With MHT Algorithm

Jayapandian¹

2020

IJC

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Cloud computing is dealing with large amount of data during data communication. This data processing is named as big data. The big data is growth of the demand in accessing the storage, computation and communication. This big data has the major defects. A raising issue in emerging big data is cost minimization. The architecture of big data ranges over multiple machines and cluster which have sub system. The major challenge of this big data is pre-processing and analysing the data patterns. This research article is dealing with different data pre-processing and secure data storage. There are many research challenges during this data process. The possible gap and drawbacks in the technology are identified through this survey and the efficient big data service is provided through MHT and AES algorithm. The main aim of this proposed method is to provide better data security during larger data process. The proposed hybrid MHT with AES algorithm is to minimize the encryption and decryption time apart from that it reduces the attacker ratio. All these parameters automatically increase the Quality of Service.

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“…Cloud computing is a new paradigm of a service delivery model. 1,2 The primary aim of cloud computing is providing on-demand, reliable, scalable, and available services in distributed environments. [3][4][5] Recently, it has gained high popularity for its efficient resource usage and convenient service access.…”

Section: Introductionmentioning

confidence: 99%

A method for virtual machine migration in cloud computing using a collective behavior‐based metaheuristics algorithm

Sha

Ebadi

Mavaluru

et al. 2019

Concurrency and Computation

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Summary Due to the growth of applications and the integration of new customers into the world of computing systems, computing needs to be changed and to become more powerful and flexible than before. Meanwhile, cloud computing is presented as a model beyond a system that is currently capable of answering most request needs. Flexible infrastructure for cloud computing and virtualization technology provide new features to support business activities. Clouds are a very important topic that used secure management tools for storage, security and securing data centers in a flexible manner. One of the important matters in cloud technologies is virtual machine migration (VMM). There are different ways to implement the VMM, but because of the limitation of resources' energy, energy management is also very important and challenging. Due to the NP‐hard nature of this problem, this paper presents an energy‐aware VMM engine for cloud computing using the discrete bacterial foraging algorithm as a new collective behavior‐based metaheuristics algorithm. The CloudSim simulator is employed to investigate the efficiency of this method. The obtained results have shown that the proposed method improves the energy consumption and the migration count.

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Query optimization mechanisms in the cloud environments: A systematic study

Cited by 24 publications

References 88 publications

Decentralized and Privacy-Preserving Public Auditing for Cloud Storage Based on Blockchain

Decentralized and Privacy-Preserving Public Auditing for Cloud Storage Based on Blockchain

Securing Cloud Data Against Cyber-Attacks Using Hybrid Aes With MHT Algorithm

A method for virtual machine migration in cloud computing using a collective behavior‐based metaheuristics algorithm

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