Visible to the public Markov Augmented Neural Networks for Streaming Video Classification

TitleMarkov Augmented Neural Networks for Streaming Video Classification
Publication TypeConference Paper
Year of Publication2019
AuthorsShaout, Adnan, Crispin, Brennan
Conference Name2019 International Arab Conference on Information Technology (ACIT)
Date Publisheddec
PublisherIEEE
ISBN Number978-1-7281-3010-1
Keywordscontent providers, decision theory, deep packet inspection, deep packet inspection techniques, image classification, Inspection, Internet, internet providers, IP addresses, IP networks, machine learning, Markov augmented neural networks, Markov Decision Process, Markov processes, neural nets, Neural networks, port scanning, pubcrawl, resilience, Resiliency, Scalability, streaming video classification, telecommunication traffic, video signal processing, video streaming, video streaming services
Abstract

With the growing number of streaming services, internet providers are increasingly needing to be able to identify the types of data and content providers that are being used on their networks. Traditional methods, such as IP and port scanning, are not always available for clients using VPNs or with providers using varying IP addresses. As such, in this paper we explore a potential method using neural networks and Markov Decision Process in order to augment deep packet inspection techniques in identifying the source and class of video streaming services.

URLhttps://ieeexplore.ieee.org/document/8991002
DOI10.1109/ACIT47987.2019.8991002
Citation Keyshaout_markov_2019