Thesis (M.S. in Computer Science)--Naval Postgraduate School, March 2004. / Thesis advisor(s): Geoffrey Xie. Includes bibliographical references (p. 155-156). Also available online.

Thesis (M.S.)--California Polytechnic State University, 2009. / Title from PDF title page; viewed on January 12, 2010. Major professor: Franz Kurfess, Ph.D. "Presented to the faculty of California Polytechnic State University, San Luis Obispo." "In partial fulfillment of the requirements for the degree [of] Master of Science in Computer Science." "December 2009." Includes bibliographical references (p. 125-135).

Thesis (M. Phil.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 148-153).

published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

Approved for public release, distribution is unlimited / Inter-domain routing connects individual pieces of Internet topology, creating an integral, global data delivery infrastructure. Currently, this critical function is performed by the Border Gateway Protocol (BGP) version 4 [RFC1771]. Like all routing protocols, BGP is vulnerable to instabilities that reduce its effectiveness. Among the causes of these instabilities are those which are maliciously induced. Although there are other causes, e.g., natural events and network anomalies, this thesis will focus exclusively on maliciously induced instabilities. Most current models that attempt to predict a BGP routing instability confine their focus to either macro- or micro-level metrics, but not to both. The inherent limitations of each of these forms of metric gives rise to an excessive rate of spurious alerts, both false positives and false negatives. It is the original intent of this thesis to develop an improved BGP instability prediction model by statistically combining BGP instability metrics with user level performance metrics. The motivation for such a model is twofold. 1) To provide sufficient prior warning of impending failure to facilitate proactive protection measures. 2) To improve warning reliability beyond existing models, by demonstrably reducing both false positives and false negatives. However, our analysis of actual network trace data shows that a widely used BGP instability metric, the total number of update messages received in a time period, is not a good indicator of future user level performance. / Civilian, Department of Defense