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Distributed type big data system risk recognition method based on LSA-GCC

A risk identification, big data technology, applied in the field of cloud computing, can solve problems such as unsatisfactory WebService effect

Inactive Publication Date: 2015-05-20
XIAMEN UNIV +1
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  • Abstract
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  • Claims
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Problems solved by technology

Even though the existing WebService security technology is mature and can solve some security problems, the effect of WebService oriented to the cloud computing environment is not satisfactory.

Method used

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  • Distributed type big data system risk recognition method based on LSA-GCC
  • Distributed type big data system risk recognition method based on LSA-GCC
  • Distributed type big data system risk recognition method based on LSA-GCC

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Embodiment Construction

[0088] The present invention will be further described in conjunction with the accompanying drawings and specific embodiments.

[0089] Cloud computing is a new generation product of cluster computing, parallel computing, and grid computing, which integrates various concepts and technologies of distributed computing. The cloud computing environment typically presents the characteristics of large-scale distribution, complex structure, diversified architecture, dynamic computing and service virtualization, among which virtualization technology is one of the key technologies of cloud computing. Virtualization puts forward higher security and quality requirements for service-oriented (WebService) cloud computing system suppliers, while traditional research mostly focuses on information system risk assessment and network intrusion detection, lacking in-depth research on cloud computing. Therefore, it is necessary to conduct risk assessment research on service-oriented cloud computi...

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Abstract

The invention discloses a distributed type big data system risk recognition method based on LSA-GCC which comprises the first step of establishing an LSA-GCC model, the LSA-GCC model is used for mapping a data set to a semantic space, and classifying the data set by a clustering algorithm, extracting a specifically classified prototype vector from clustering results, giving a certain weight to each classification, and establishing an initial prototype vector model; the second step of conducting feedforward recognition to a risk through an LSA-SAM safety recognition model, the LSA-SAM safety recognition model conducts information system risk evaluation based on the LSA-GCC model, after data to be evaluated are mapped to the same semantic space, calculating the prototype vector of the each classification and obtaining similarity belonging to the classification, obtaining a cumulative sum of the similarity and the weight of the corresponding classification, finally obtaining risk value of the data to be evaluated by averaging, namely obtaining the risk value at an arrival moment of the data.

Description

technical field [0001] The invention belongs to the technical field of cloud computing, and relates to a risk assessment research for a service-oriented cloud computing system, specifically a LSA-GCC (Latent Semantic Analysis-Generalized Clusterbased Classifier, latent semantic analysis and generalized clustering classifier) risk identification method. Background technique [0002] In recent years, the rapid development of cloud computing technology has become the focus of industry, academia, government and other circles. The essence of cloud computing is a dynamic resource combination and service technology, and a large number of virtualized components form a resource pool to allocate computing tasks, so that users can obtain cloud computing services on demand. Cloud computing is also a comprehensive application of parallel computing, utility computing, grid computing and virtualization technology. According to the type of service, it is mainly divided into three hierarchi...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCH04L41/145G06F16/35H04L41/069
Inventor 林凡王备战吴鹏程夏侯建兵
Owner XIAMEN UNIV
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