News

Dr. José R. Ortiz-Ubarri presented the work Toa: A Web-Based NetFlow Data Network Monitoring System at Scale at the 2015 IEEE Big Data Congress that took place from Saturday, June 27 through Thursday, July 2, 2015  in New York, at the at the Broadway Millenium Hotel.  The Toa system was developed by the undergraduate research students Albert Maldonado, Eric Santos, and Jhensen Grullón, and the also supervisors Dr. José Ortiz-Ubarri and Dr. Humberto Ortiz-Zuazaga at the Computer Security Lab of the Computer Science department of the University of Puerto Rico. 

Toa consists of a collection of scripts that automatically parse NetFlow data, store this information in a database system, and generate interactive line charts for network visualization analytics. The system is pseudo real time, meaning that it continuously updates the interactive charts from NetFlow data that is generated every five minutes. Toa also provides an interface to generate customized charts from the data stored in the database, and plugins that connect the visualization charts with the NetFlow data file for more in depth visualizations and analysis. The Toa web GUI presents users with the following network traffic visualization options: (1) per network label (interface, Autonomous System [AS], or network block) traffic, (2) per-port traffic for each network label, (3) network label to network label traffic, (4) customized charts from the database data, and (5) plugins for in-depth analysis of the NetFlow data file. (https://github.com/cslab-uprrp/toa)

References:

2015 IEEE Big Data Congress, http://www.ieeebigdata.org/2015/

Toa repository: https://github.com/cslab-uprrp/toa