Abstract

In this work, we propose three important contributions needed in the process of improving the security of the critical infrastructure: metrics, measurement, and analysis. To improve security, metrics are key to ensuring the accuracy of the assessment and evaluation. Measurements are the core of the process of identifying the causality and effectiveness of various behaviors, and accurate measurement with the right assumptions is a cornerstone for accurate analysis. Finally, contextualized analysis essential for understanding measurements. Different results can be derived for the same data according to the analysis method, and it can serve as a basis for understanding and improving systems security. In this dissertation, we look at whether these key concepts are well demonstrated in existing (networked) systems and research products. In the first thrust, we verified the validity of volume-based contribution evaluation metrics used in threat information sharing systems. Further, we proposed a qualitative evaluation as an alternative to supplement the shortcomings of the volume-based evaluation method. In the second thrust, we measured the effectiveness of the low-rate DDoS attacks in a realistic environment to highlight the importance of establishing assumptions grounded in reality for measurements. Moreover, we theoretically analyzed the low-rate DDoS attacks and conducted additional experiments to validate them. In the last thrust, we conducted a large-scale measurement and analyzed the behaviors of open resolvers, to estimate the potential threats of them. We then went beyond just figuring out the number of open resolvers and explored new implications that the behavioral analysis could provide. We also experimentally shown the existence of forwarding resolvers and their behavior by precisely analyzing DNS resolution packets.

Notes

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Graduation Date

2020

Semester

Summer

Advisor

Mohaisen, David

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Computer Science

Degree Program

Computer Science

Format

application/pdf

Identifier

CFE0008214; DP0023568

URL

https://purls.library.ucf.edu/go/DP0023568

Language

English

Release Date

August 2020

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

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