Theses and dissertations

This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students. 

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Data Driven Game Theoretic Cyber Threat Mitigation

Description
Penetration testing is regarded as the gold-standard for understanding how well an organization can withstand sophisticated cyber-attacks. However, the recent prevalence of markets specializing in zero-day exploits on the darknet make exploits widely available to potential attackers. The cost associated with these sophisticated kits generally precludes penetration testers from simply…

Penetration testing is regarded as the gold-standard for understanding how well an organization can withstand sophisticated cyber-attacks. However, the recent prevalence of markets specializing in zero-day exploits on the darknet make exploits widely available to potential attackers. The cost associated with these sophisticated kits generally precludes penetration testers from simply obtaining such exploits – so an alternative approach is needed to understand what exploits an attacker will most likely purchase and how to defend against them. In this paper, we introduce a data-driven security game framework to model an attacker and provide policy recommendations to the defender. In addition to providing a formal framework and algorithms to develop strategies, we present experimental results from applying our framework, for various system configurations, on real-world exploit market data actively mined from the darknet.
ContributorsRobertson, John James (Author) / Shakarian, Paulo (Thesis director) / Doupe, Adam (Committee member) / Electrical Engineering Program (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Visualizing Information Flow Graph-Based Approach to Tracing Data Dependencies for Binary Analysis

Description
Binary analysis and software debugging are critical tools in the modern softwaresecurity ecosystem. With the security arms race between attackers discovering and exploiting vulnerabilities and the development teams patching bugs ever-tightening, there is an immense need for more tooling to streamline the binary analysis and debugging processes. Whether attempting to find the root…

Binary analysis and software debugging are critical tools in the modern softwaresecurity ecosystem. With the security arms race between attackers discovering and exploiting vulnerabilities and the development teams patching bugs ever-tightening, there is an immense need for more tooling to streamline the binary analysis and debugging processes. Whether attempting to find the root cause for a buffer overflow or a segmentation fault, the analysis process often involves manually tracing the movement of data throughout a program’s life cycle. Up until this point, there has not been a viable solution to the human limitation of maintaining a cohesive mental image of the intricacies of a program’s data flow. This thesis proposes a novel data dependency graph (DDG) analysis as an addi- tion to angr’s analyses suite. This new analysis ingests a symbolic execution trace in order to generate a directed acyclic graph of the program’s data dependencies. In addition to the development of the backend logic needed to generate this graph, an angr management view to visualize the DDG was implemented. This user interface provides functionality for ancestor and descendant dependency tracing and sub-graph creation. To evaluate the analysis, a user study was conducted to measure the view’s efficacy in regards to binary analysis and software debugging. The study consisted of a control group and experimental group attempting to solve a series of 3 chal- lenges and subsequently providing feedback concerning perceived functionality and comprehensibility pertaining to the view. The results show that the view had a positive trend in relation to challenge-solving accuracy in its target domain, as participants solved 32% more challenges 21% faster when using the analysis than when using vanilla angr management.
ContributorsCapuano, Bailey Kellen (Author) / Shoshitaishvili, Yan (Thesis advisor) / Wang, Ruoyu (Thesis advisor) / Doupe, Adam (Committee member) / Arizona State University (Publisher)
Created2022