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

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.