SWIFTNet Test Logs Dashboard: Using JavaScript to Pull and Display Test Logs; Interconnected Vulnerabilities: An Actor-Network Theory Analysis of the 23andMe Data Breach

Author:
Allard, Tiara, School of Engineering and Applied Science, University of Virginia
Advisors:
Vrugtman, Rosanne
Laugelli, Benjamin
Abstract:

My technical capstone project at SWIFT and my STS research on the 23andMe data breach may initially appear distinct, but a retrospective application of Bruno Latour’s Actor-Network Theory (ANT) reveals thematic connections regarding the formation and function of technological networks. In my technical project, I focused on building a user-friendly interface for viewing test logs at SWIFT. This task involved coordinating with developers, testers, and various software tools. However, at the time, I did not frame this project within the ANT framework. My subsequent introduction to ANT in my STS research provided a new lens to analyze technological interactions. In studying the 23andMe data breach, I applied ANT to understand how different actors—both human and non-human—interacted within the network, leading to the breach. Looking back at my technical work through the ANT framework, I can now see how my seemingly narrow role was integral to a larger network aimed at improving software testing and security. This network involved various actors whose roles and interactions worked together to achieve the common goal of enhancing engineering standards by increasing efficiency.

In my technical capstone project, I developed a JavaScript-based dashboard for SWIFTNet's Testing Automation team to efficiently manage and analyze test logs. The project involved integrating various software tools and frameworks, such as Next.js for server-side operations, to create a seamless user interface. Key components included log-pulling functionality, interactive tables, and dynamic filters, which collectively improved the workflow and productivity of the team. This technology stack, alongside my collaboration with mentors and team members, created the network that facilitated the transformation of the testing process at SWIFT.

My STS research paper, "Interconnected Vulnerabilities: An Actor-Network Theory Analysis of the 23andMe Data Breach," investigates the interdependencies within the network of actors that contributed to the data breach at 23andMe. Utilizing ANT, I explored how the network composed of the company, its technology, customers, and regulatory frameworks interacted to shape the event. The paper argues that the breach was not merely a failure of technology or the users alone, but a result of complex interactions among all these actors, demonstrating the network's influence on the vulnerability of data security.

Working on my technical capstone project at SWIFT followed by my STS research paper this semester provided insights into the complexities of technological networks. While developing the testing dashboard, I was focused on the immediate goal of enhancing the team's workflow through a user-friendly interface. However, applying the ANT lens from my STS research, I can see how I was part of an actor-network brought together with the common goal of improving team productivity, software quality and security standards. I had not initially thought of the technology stack as part of the team, but in retrospect, the choice of technology does clearly play a role in achieving the common goal, along with all the other actors, both within my team and beyond. For example, I can now identify a negotiation that occurred in this network; a compromise that the human actors had to make was to switch from using React.js to Next.js as the former framework did not have server-side capabilities. This understanding will inform my approach to future technical projects, emphasizing a holistic view of the various elements involved and their translations and negotiations.

Degree:
BS (Bachelor of Science)
Keywords:
javascript, data breach, actor network theory, user configuration
Notes:

School of Engineering and Applied Science

Bachelor of Science in Computer Science

Technical Advisor: Rosanne Vrugtman

STS Advisor: Benjamin Laugelli

Language:
English
Rights:
All rights reserved (no additional license for public reuse)
Issued Date:
2024/05/09