A machine learning application for reducing the security risks in hybrid cloud networks

Август 12, 2022

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A machine learning application for reducing the security risks in hybrid cloud networks

Содержание

2. Outline: Introduction Objectives Methodology Results and conclusion References
4. Introduction Cloud computing facilitates enormous support of the public, business and emerging applications.
5. Introduction In cloud network environment, the data security is playing crucial roles.
6. Deduplication process
7. Objectives Introduce a new access control mechanism which is working dynamic in nature that is based
8. System architecture
9. Proposed work DDPA DSRBACA
10. DDPA:
11. DDPA:
12. Dynamic spatial role based access control algorithm
13. DSRBACA:
16. Results and conclusion A new machine learning application has been developed for providing security to the
17. References 1. Alabdulatif A, Kumarage H, Khalil I, Yi X (2017) Privacy-preserving anomaly detection in cloud
19. Скачать презентацию

Слайд 2

Outline:
Introduction
Objectives
Methodology
Results and conclusion
References

Слайд 3

Слайд 4

Introduction
Cloud computing facilitates enormous support of the public, business and emerging

applications.

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Introduction
In cloud network environment, the data security is playing crucial roles.

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Deduplication process

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Objectives
Introduce a new access control mechanism which is working dynamic

in nature that is based on time and place.
Create a new deduplication process for storing the data securely and also for avoiding the data duplication during the retrieval process

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System architecture

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Proposed work
DDPA
DSRBACA

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DDPA:

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DDPA:

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Dynamic spatial role based access control algorithm

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DSRBACA:

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Results and conclusion
A new machine learning application has been developed for

providing security to the hybrid cloud networks while storing the data and retrieving or accessing the data from cloud databases.

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References
1. Alabdulatif A, Kumarage H, Khalil I, Yi X (2017)

Privacy-preserving anomaly detection in cloud with lightweight homomorphic encryption. J Comput Syst Sci 90:28–45
2. Elumalaivasan P, Kulothungan K, Ganapathy S, Kannan A (2016) Trust based Ciphertext policy attribute based encryption techniques for decentralized disruption tolerant networks. Aust J Basic Appl Sci 10(2):18–26
3. Gordon A (2016) The hybrid cloud security professional. IEEE Cloud Comput 3(1):82–86
4. Helmi AM, Farhan MS, Nasr MM (2018) A framework for integrating geospatial information systems and hybrid cloud computing. Comput Electr Eng 67:145–158
5. Hudic A, Smith P, Weippl ER (2017) Security assurance assessment methodology for hybrid clouds. Comput Sec 70:723–743