Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)


School of Computing

Committee Chair/Advisor

Long Cheng

Committee Member

Richard Brooks

Committee Member

Abolfazl Razi

Committee Member

Zhenkai Zhang


Security testing consists of automated processes, like Dynamic Application Security Testing (DAST) and Static Application Security Testing (SAST), as well as manual offensive security testing, like Penetration Testing and Red Teaming. This nonautomated testing is frequently time-constrained and difficult to scale. Previous literature suggests that most research is spent in support of improving fully automated processes or in finding specific vulnerabilities, with little time spent improving the interpretation of the scanned attack surface critical to nonautomated testing. In this work, agglomerative hierarchical clustering is used to compress the Internet-facing hosts of 13 representative companies as collected by the Shodan search engine, resulting in an average 89% reduction in attack surface complexity. The work is then extended to map network services and also analyze the characteristics of the Log4Shell security vulnerability and its impact on attack surface mapping. The results highlighted outliers indicative of possible anti-patterns as well as opportunities to improve how testers and tools map the web attack surface. Ultimately the work is extended to compress web attack surfaces based on security relevant features, demonstrating via accuracy measurements not only that this compression is feasible but can also be automated. In the process a framework is created which could be extended in future work to compress other attack surfaces, including physical structures/campuses for physical security testing and even humans for social engineering tests.

Author ORCID Identifier




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