Software Engineering Institute | Carnegie Mellon University
Software Engineering Institute | Carnegie Mellon University

Digital Library

Ron McLeod (Corporate Development Telecom Applications Research Alliance)
January 2013 - Presentation Presenting Mongoose A New Approach to Traffic Capture

Topics: Network Situational Awareness

In this presentation, the authors describe Mongoose, a tool for monitoring the activity of the network from outside the network.

January 2009 - Presentation Traffic Clusters in Networks of Convenience

Topics: Network Situational Awareness

In this presentation, the authors describe the Mission Diagnostic, applying it, and lessons learn in applying it.

January 2008 - Presentation One Year of Peer to Peer

Topics: Network Situational Awareness

In this presentation, Ron McLeod profiles the growth in peer-to-peer applications on a sample network and describes the increase in the diversity of traffic.

October 2006 - Presentation A Traffic Analysis of a Small Private Network Compromised by an Online Gaming Host (Presentation)

Topics: Network Situational Awareness

In this presentation, Ron McLeod describes the results of an analysis to investigate performance issues on a small private network.

October 2006 - White Paper A Traffic Analysis of a Small Private Network Compromised by an Online Gaming Host (White Paper)

Topics: Network Situational Awareness

In this paper, Ron McLeod describes a network traffic capture and analysis used to investigate network performance issues of a small private network.

October 2006 - Presentation Anomaly Detection Through Blind Flow Analysis Inside a Local Network (Presentation)

Topics: Network Situational Awareness

In this presentation, the authors describe how hosts may be clustered into user workstations, servers, printers, and hosts compromised by worms.

October 2006 - White Paper Anomaly Detection Through Blind Flow Analysis Inside a Local Network (White Paper)

Topics: Network Situational Awareness

In this paper, the authors describe how hosts may be clustered into user workstations, servers, printers, and hosts compromised by worms.