Improving network security by sanitizing network topological information to encapsulate particular network topology
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Date
JUNE, 2019
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Abstract
Securing data is crucial in a world where attackers will attempt to gain access to personal and
business information that, for privacy reasons, we want to protect. Information on a network
topology can be used by an adversary to undermine a network. To preserve this information,
access to the data can be restricted. What if, however, we want to share the information with
another party to allow analysis on the data? How can we ensure that the privacy of our data is
protected while still providing accurate analysis? Summarizing the information of network
topology may not allow for any analysis to be performed on the data. Sanitization, on the other
hand, explores methods to mask the network topology information in such a way that the
network’s characteristics will be hiding while still providing an analyst with data on which she
can run statistics. There exists a tenuous balance between the need for privacy of the unsanitized
network data and the accuracy of the analysis on the sanitized data. The goal is to effectively
hide the raw data while the analysis on the sanitized data produces the same results as if
performed on the raw data. By exploring the network characteristics, we can determine possible
statistics that may derive from the data. We proposed a standard syntax for defining a network.
From the syntax and the topology characteristics, sanitization schemes are detailed explaining
the balance between privacy and statistical accuracy. IP addressing ramifications and the
concerns when sanitizing are also identified.
Description
A thesis submitted to the Department of Computer Science, in partial fulfillment of the requirements for the award of master of science degree in information technology
Keywords
Network security, Network topology, Sanitization