Security of Applications Involving Multiple Organizations and Order Preserving Encryption in Hybrid Cloud Environments

Ahmadian, Mohammad; Paya, Ashkan; Marinescu, Dan C.

doi:10.1109/ipdpsw.2014.102

Cited by 13 publications

(5 citation statements)

References 9 publications

(4 reference statements)

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“…The data transfer among the tasks in a workflow depends on the workflow structure. The privacy protection strategies can be divided into the following three categories: data encryption [9], data anonymization [10], and task classification [11]- [13]. Liu et al [14] presented a new searchable encryption scheme that guarantees data privacy as well as efficient data search and retrieval in a distributed environment.…”

Section: Related Workmentioning

confidence: 99%

Hybrid Cloud Workflow Scheduling Method With Privacy Data

2020

IEEE Access

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Privacy protection is an important problem in workflow scheduling, for which scheduling tasks with privacy constraints to reliable resources is essential. In this article, we consider the scheduling problem of Spark applications in a hybrid cloud with deadline and privacy constraints. A scheduling algorithm framework is proposed, which consists of four algorithm components. Candidate strategies are developed for each algorithm component. The components and parameter values are statistically calibrated over a comprehensive set of random instances. The proposed algorithm is compared to modified classical algorithms for similar problems. The experimental results indicate that the proposed algorithm outperforms the compared algorithms under different application scales, deadlines, and private VMs INDEX TERMS Spark, privacy task, cost optimization, hybrid cloud.

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Section: Related Workmentioning

confidence: 99%

Hybrid Cloud Workflow Scheduling Method With Privacy Data

2020

IEEE Access

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“…Unfortunately, this method does not give the detailed construction of designed algorithms. Ahmadian et al [10] discussed a hybrid clouds based architecture to provide an ideal environment for cooperation of multiple organizations. In this scheme, trusted private cloud processes sensitive data and public cloud adopts order preserving encryption to process data.…”

Section: Related Workmentioning

confidence: 99%

Adaptive Secure Cross-Cloud Data Collaboration with Identity-Based Cryptography and Conditional Proxy Re-Encryption

Huang

Yue

et al. 2018

Security and Communication Networks

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Data collaboration in cloud computing is more and more popular nowadays, and proxy deployment schemes are employed to realize cross-cloud data collaboration. However, data security and privacy are the most serious issues that would raise great concerns from users when they adopt cloud systems to handle data collaboration. Different cryptographic techniques are deployed in different cloud service providers, which makes cross-cloud data collaboration to be a deeper challenge. In this paper, we propose an adaptive secure cross-cloud data collaboration scheme with identity-based cryptography (IBC) and proxy re-encryption (PRE) techniques. We first present a secure cross-cloud data collaboration framework, which protects data confidentiality with IBC technique and transfers the collaborated data in an encrypted form by deploying a proxy close to the clouds. We then provide an adaptive conditional PRE protocol with the designed full identity-based broadcast conditional PRE algorithm, which can achieve flexible and conditional data re-encryption among ciphertexts encrypted in identity-based encryption manner and ciphertexts encrypted in identity-based broadcast encryption manner. The extensive analysis and experimental evaluations demonstrate the well security and performance of our scheme, which meets the secure data collaboration requirements in cross-cloud scenarios.

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“…[11 researchers proposes a system design that deals with big data of the banking system while keeping under consideration the complexity and the multiple requirements a banking system must have requirements in processing, privacy and safety and even in storage. [14] introduced a privacy approach for big data applications including the financial ones that focuses on the concept of Order Preserving Encryption (OPE) where some fields are encrypted according to its sensitivity. In addition to that, the approach is concerned with information shared between multiple organizations and for that, authors suggest having private information on private clouds where it is strictly treated and processed.…”

Section: Financementioning

confidence: 99%