OntoDS: An Ontology-Aware Distributed Storage Scheme for RDF Graphs

2019 ◽  
pp. 645-659
Author(s):  
Baozhu Liu ◽  
Xin Wang ◽  
Yajun Yang ◽  
Yunpeng Chai
Keyword(s):  
Distributed Storage ◽  
Storage Scheme ◽  
Rdf Graphs

A new distributed storage scheme for cluster video server

2005 ◽  
Vol 51 (2) ◽  
pp. 79-94 ◽  
Author(s):  
Xiaofei Liao ◽  
Hai Jin
Keyword(s):  
Distributed Storage ◽  
Video Server ◽  
Storage Scheme

HDStore: An SSD/HDD Hybrid Distributed Storage Scheme for Large-Scale Data

2014 ◽  
pp. 209-220 ◽  
Author(s):  
Zhijie Feng ◽  
Zhiyong Feng ◽  
Xin Wang ◽  
Guozheng Rao ◽  
Yazhou Wei ◽  
...  
Keyword(s):  
Large Scale ◽  
Distributed Storage ◽  
Large Scale Data ◽  
Storage Scheme ◽  
Scale Data

Cellular automata based secure distributed storage scheme with integrity proof

2017 ◽  
Vol 59 ◽  
pp. 291-304 ◽  
Author(s):  
Yousheng Zhou ◽  
Feng Wang ◽  
Fei Tang ◽  
Xiaojun Wang
Keyword(s):  
Cellular Automata ◽  
Distributed Storage ◽  
Storage Scheme

scholarly journals Protection of Sensitive Data in Industrial Internet Based on Three-Layer Local/Fog/Cloud Storage

2020 ◽  
Vol 2020 ◽  
pp. 1-16 ◽  
Author(s):  
Jing Liu ◽  
Changbo Yuan ◽  
Yingxu Lai ◽  
Hua Qin
Keyword(s):  
Real Time ◽  
Data Protection ◽  
Cloud Storage ◽  
Distributed Storage ◽  
Sensitive Information ◽  
Sensitive Data ◽  
Industrial Data ◽  
Threat Model ◽  
Industrial Internet ◽  
Storage Scheme

Industrial Internet technology has developed rapidly, and the security of industrial data has received much attention. At present, industrial enterprises lack a safe and professional data security system. Thus, industries urgently need a complete and effective data protection scheme. This study develops a three-layer framework with local/fog/cloud storage for protecting sensitive industrial data and defines a threat model. For real-time sensitive industrial data, we use the improved local differential privacy algorithm M-RAPPOR to perturb sensitive information. We encode the desensitized data using Reed–Solomon (RS) encoding and then store them in local equipment to realize low cost, high efficiency, and intelligent data protection. For non-real-time sensitive industrial data, we adopt a cloud-fog collaborative storage scheme based on AES-RS encoding to invisibly provide multilayer protection. We adopt the optimal solution of distributed storage in local equipment and the cloud-fog collaborative storage scheme in fog nodes and cloud nodes to alleviate the storage pressure on local equipment and to improve security and recoverability. According to the defined threat model, we conduct a security analysis and prove that the proposed scheme can provide stronger data protection for sensitive data. Compared with traditional methods, this approach strengthens the protection of sensitive information and ensures real-time continuity of open data sharing. Finally, the feasibility of our scheme is validated through experimental evaluation.

Research on Email-based Distributed Storage Scheme

2013 ◽  
Vol 8 (7) ◽  
pp. 1109-1116
Author(s):  
Bochuan Yang ◽  
Hu Wen
Keyword(s):  
Distributed Storage ◽  
Storage Scheme

scholarly journals A Three-Layer Privacy Preserving Cloud Storage Scheme Based on Computational Intelligence in Fog Computing

2020 ◽  
Vol 8 (6) ◽  
pp. 451-455
Keyword(s):  
Cloud Storage ◽  
Distributed Storage ◽  
Fog Computing ◽  
Good Judgment ◽  
Security Assurance ◽  
Course Of Action ◽  
Cloud Server ◽  
Storage Scheme ◽  
Cloud Servers ◽  
Unstructured Information

Late years witness the improvement of distributed computing innovation. With the hazardous development of unstructured information, distributed storage innovation improves advancement. Notwithstanding, in current stockpiling pattern, client's information is completely put away in cloud servers. At the end of the day, clients lose their privilege of control on information and face security spillage chance. Conventional security assurance plans are normally founded on encryption innovation, yet these sorts of strategies can't viably oppose assault from within cloud server. So as to take care of this issue, we propose a three-layer stockpiling structure dependent on mist registering. The proposed structure can both exploit distributed storage and secure the protection of information. By at that point, we can place a little piece of information in neighborhood machine and mist server so as to ensure the security. In like manner, in context on computational information, this tally can figure the assignment degree put aside in cloud, darkness, and near to machine, autonomously. Through the theoretical security appraisal and primer assessment, the good judgment of our course of action has been supported, which is actually a historic Added to current dispersed amassing plot.

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