Degree Type

Dissertation

Date of Award

2003

Degree Name

Doctor of Philosophy

Department

Electrical and Computer Engineering

First Advisor

Arun K. Somani

Abstract

An All-Optical Network (AON) is a network in which data does not undergo optical-to-electrical (O-E) or electrical-to-optical (E-O) conversion within the network. Although AONs are a viable technology for future telecommunication and data networks, little attentions has been devoted to the intrinsic differences between AONs and existing existing electro-optic/electronic networks in issues of security management. Without. O-E-O conversion, many security vulnerabilities that do not exist in traditional networks are created. Transparency and non-regeneration features make attack detection and localization difficult. However, it is important to detect and localize an attack connection quickly in a transparent AON;Among all attack methods, crosstalk attack has the highest damage capabilities. Therefore, we specifically focus on crosstalk attacks in this dissertation. We show that it is possible to effectively reduce the number of monitors while still retaining all diagnostic capabilities. We make the following contributions: (1) We provide a crosstalk attack model and a monitoring model. (2) Based on these models, we prove necessary and sufficient conditions for a both one attack and more than one (i.e., k-crosstalk) attack diagnostic network. The key ideas used in our solution are to employ the status of connections as diagnostic data. (3) We develop efficient monitor placement policies, test connection setup policies, and routing policies for such a network. These conditions lead to efficient k-attack detection and diagnosis algorithms. (4) Finally, we analyze the performance of these algorithms;By these conditions and policies, we prove that the concept of a sparse monitor system for monitoring and localizing crosstalk attacks in AON is not only possible but also feasible.

DOI

https://doi.org/10.31274/rtd-180813-16496

Publisher

Digital Repository @ Iowa State University, http://lib.dr.iastate.edu/

Copyright Owner

Tao Wu

Language

en

Proquest ID

AAI3308906

File Format

application/pdf

File Size

91 pages

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