Minjun (Elena) Long

I am a fourth-year PhD candidate in Computer Science at the University of Virginia, advised by Professor David Evans in the Security Research Group. My research focuses on systematic evaluation and empirical analysis of security- and privacy-critical systems, with an emphasis on understanding when claimed guarantees break down in real-world settings.

Across my work, I have been consistently interested in the gap between what systems are designed or claimed to do and how they actually behave in practice. Early in my research, this led me to large-scale empirical studies of online platforms and web privacy protocols, where formal guarantees often rely on assumptions that are difficult to validate after deployment. Later, while studying audio-visual deepfake detection, I became increasingly aware that strong benchmark performance does not necessarily imply that a model has learned the semantic properties we expect, which further shaped my focus on evaluation methodology and failure analysis.

More recently, my work has centered on the evolution of host-based intrusion detection system, where security knowledge itself changes over time in response to adversaries, data drift, and engineering constraints. Through this lens, I study how detection rules are authored, modified, and revised in practice, and what these changes reveal about detection effectiveness, evaluation blind spots, and long-term maintainability.

I am actively seeking research internships and full-time roles where I can apply empirical evaluation and security analysis to real systems and datasets, working closely with engineering and threat assessment teams to surface actionable insights. I am particularly interested in industrial research roles that emphasize security effectiveness, detection efficacy, trustworthy system evaluation, and empirical analysis of complex deployed systems.

My Chinese name is written as 龙玟君, and I go by Elena in my daily life. I drew my self-portrait on the right with Procreate, celebrating the Year of the Snake (2025).