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

Digital Library

Javascript is currently disabled for your browser. For an optimal search experience, please enable javascript.

Advanced Search

Basic Search

Content Type

Topics

Publication Date

Showing 1 - 6 of 6 results for the Author - michael collins , Type - White Paper

White Paper | October 2015 - White Paper Effective Insider Threat Programs: Understanding and ... By Andrew P. Moore, William E. Novak, Matthew L. Collins, Randall F. Trzeciak, Michael C. Theis

In this paper, the authors describe the potential ways an insider threat program (InTP) could go wrong and to engage the community to discuss its concerns.

White Paper | September 2006 - White Paper Finding Peer-To-Peer File-Sharing Using Coarse Network ... By Michael Collins, Michael K. Reiter

In this paper, the authors propose a set of tests for identifying masqueraded peer-to-peer file-sharing based on traffic summaries (flows).

White Paper | May 2004 - White Paper An Empirical Analysis of Target-Resident DoS Filters By Michael Collins, Michael K. Reiter

In this paper, the authors provide an empirical analysis of proposed techniques for filtering network traffic.

White Paper | September 2007 - White Paper Hit-List Worm Detection and Bot Identification in Large ... By M. P. Collins (Redjack), Michael K. Reiter

In this paper, the authors present a novel method for detecting hit-list worms using protocol graphs.

White Paper | June 2005 - White Paper Advanced Security Reporting Systems for Large Network ... By Michael Collins, Greg Virgin (Redjack)

In this paper, the authors describe the technologies that support an asset inventory system and enable a flexible, ad-hoc intrusion detection capability.

White Paper | July 2006 - White Paper A Model for Opportunistic Network Exploits: The Case of P2P ... By Carrie Gates, Michael Collins

In this paper, the authors present VisFlowConnect-IP, a network flow visualization tool that detects and investigates anomalous network traffic.