View in EDS

A context sensitive security framework for Enterprise multimedia placement in fog computing environment.

Saved in:
Bibliographic Details
Title: A context sensitive security framework for Enterprise multimedia placement in fog computing environment.
Authors: Gill, Harsuminder Kaur, Sehgal, Vivek Kumar, Verma, Anil Kumar
Source: Multimedia Tools & Applications; Apr2020, Vol. 79 Issue 15/16, p10733-10749, 17p
Subject Terms: FOG, PYTHON programming language, STREAMING video & television, DISTRIBUTED computing, INFORMATION sharing, VIDEO editing
Abstract: In the era of ICT, multimedia files are one of the main sources of information sharing for any enterprise located in one or more geographical locations. Online video watching and editing platforms needs to store the multimedia file close to the end user so that the latency can be minimized which in result enhances the quality of experience. Fog computing is evolved as distributed computing infrastructure located close to end user with minimum latency. As, Fog computing is distributed and can be owned by third party providers, a framework is proposed which selects the appropriate Fog computing environment for placement of multimedia files based on context and security requirements. Deep neural network is used to evaluate context parameters, explicit security requirement, file type classification, and final allocation decision. The proposed framework is tested using Juypter notebook and Python 3.6 framework for one million instances of multimedia files. It has received 84% (average of ten experimental runs) accuracy in selection of appropriate Fog layer to place a multimedia file. The Proposed framework enhances the multimedia file placement on Fog computing environment so that processing of file can be done without worrying about the security of Fog. [ABSTRACT FROM AUTHOR]
Copyright of Multimedia Tools & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Complementary Index
Description
Abstract:In the era of ICT, multimedia files are one of the main sources of information sharing for any enterprise located in one or more geographical locations. Online video watching and editing platforms needs to store the multimedia file close to the end user so that the latency can be minimized which in result enhances the quality of experience. Fog computing is evolved as distributed computing infrastructure located close to end user with minimum latency. As, Fog computing is distributed and can be owned by third party providers, a framework is proposed which selects the appropriate Fog computing environment for placement of multimedia files based on context and security requirements. Deep neural network is used to evaluate context parameters, explicit security requirement, file type classification, and final allocation decision. The proposed framework is tested using Juypter notebook and Python 3.6 framework for one million instances of multimedia files. It has received 84% (average of ten experimental runs) accuracy in selection of appropriate Fog layer to place a multimedia file. The Proposed framework enhances the multimedia file placement on Fog computing environment so that processing of file can be done without worrying about the security of Fog. [ABSTRACT FROM AUTHOR]
ISSN:13807501
DOI:10.1007/s11042-020-08649-4