Abstract
One of the corporate security challenges faced at Atlassian was the lack of visibility of third party Software-as-a-Solution (SaaS) applications integrated with authentication platforms such as Okta. To address this challenge, I developed a dashboard in Databricks to analyze app usage and authentication security and present it in a user-friendly format. The implementation of this project involved refining Splunk search queries to parse the Okta System data, contributing to the metric-cacher pipeline to transfer the data to Databricks, and writing SQL queries to generate dashboard visualizations. The dashboard analyzed over 1,000 third party SaaS applications, providing information about their authentication protocols, usage breakdown within the teams in the enterprise, and trends with multi-factor authentication (MFA) factors. To improve the dashboard, it would be beneficial to incorporate dynamic data visualizations that monitor which teams are accessing sensitive or high-tier applications and logging admin and bot accounts for auditing capabilities.
In 2019, Google announced its achievement of “quantum computing”, marking a pivotal moment in the development of the technology. Since then, the technology has advanced rapidly, with milestones such as IBM’s proposed Starling project, projected to be 20,000 times faster than current systems. However, the implications of this technology go beyond research laboratories, holding the potential to reshape international relations, compromise cybersecurity infrastructures, and threaten the privacy and security of everyday citizens. With this, I ask: what policies and sociotechnical dynamics have shaped and continue to shape the development and governance of quantum computing? How do those policies and dynamics influence who benefits from this emerging technology? I use Actor-Network Theory to examine the connections between government agencies, technologies, private companies, and policies that play a role in quantum computing’s development and trajectory. My analysis combines historical contextualization and policy evaluation to understand the original intentions of quantum computing, examine how advanced technology was often utilized as surveillance tools in the past, and determine where the majority of funding is allocated. The findings revealed the transformation of quantum computing as it went from a theoretical concept for simulating atomic particles to practical applications being shaped by actors such as the Department of Defense, IBM, and IonQ. Given the history of the United States using advanced systems to monitor marginalized communities, the technology’s ability to eventually crack all major encryption standards poses a threat to current safeguards that may be in place. It creates more room for the invasion of privacy for these targeted groups. Quantum computing and its effects are not developed in isolation and risks reproducing the same dynamics observed before in computational technologies: concentrating power, enabling surveillance, and widening social inequalities. The technology should be developed with human rights-centered design principles integrated in each step in addition to ensuring that treaties or agreements establish norms around quantum research, security, and data protection.
My technical project and STS research are conceptually connected through their shared focus on the importance of encryption standards. The technical project of creating a Databricks Dashboard represents a micro-level approach to strengthening digital security in enterprise systems, while the STS analysis focuses on a more macro level by exploring how new technologies may disrupt those systems entirely. Both projects emphasize the importance of understanding who has access to data and anticipating how future technologies might alter that landscape. Essentially, the technical project provides a more hands-on, practical case of security enhancement, while the STS project offers a theoretical lens to question what security will entail in a post-quantum world.
