Summaries - Office of Research & Innovation
Back Network Traffic Clustering and Cluster Characterization
|Division||Graduate School of Operational & Information Sciences|
Monaco, John V.
|Sponsor||Army Network Enterprise Technology Command (Army)|
|Summary||This project will focus on network traffic clustering using machine learning techniques and characterization of clusters to identify the sources of data that form individual clusters. Characterization of clusters maybe based on the nature of activity performed (such as video conferencing, web access, and email) and can help us identify associated types of devices (such as printers, surveillance cameras and other machinery) and types of activity (such as voice over IP, email and web access). Further, such characterization could be useful for identifying users on the network and the type of work they may be engaged in. This basic understanding can then be used to prioritize network traffic (or bandwidth allocation) to support the mission objectives. We will evaluate our approach within the context of a live network, considering effects such as number of active users, time of day, number of unique devices, network bandwidth.|
|Publications||Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal|
|Data||Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal|