6 papers
An Ethically Grounded LLM-Based Approach to Insider Threat Synthesis and Detection
Haywood Gelman, John D. Hastings, David Kenley
Insider threats are a growing organizational problem due to the complexity of identifying their technical and behavioral elements. A large research body is dedicated to the study o…
LibLMFuzz: LLM-Augmented Fuzz Target Generation for Black-box Libraries
Ian Hardgrove, John D. Hastings
A fundamental problem in cybersecurity and computer science is determining whether a program is free of bugs and vulnerabilities. Fuzzing, a popular approach to discovering vulnera…
A Systematic Review and Taxonomy for Privacy Breach Classification: Trends, Gaps, and Future Directions
Clint Fuchs, John D. Hastings
In response to the rising frequency and complexity of data breaches and evolving global privacy regulations, this study presents a comprehensive examination of academic literature…
Scalable and Ethical Insider Threat Detection through Data Synthesis and Analysis by LLMs
Haywood Gelman, John D. Hastings
Insider threats wield an outsized influence on organizations, disproportionate to their small numbers. This is due to the internal access insiders have to systems, information, and…
Toward an Insider Threat Education Platform: A Theoretical Literature Review
Haywood Gelman, John D. Hastings, David Kenley +1
Insider threats (InTs) within organizations are small in number but have a disproportionate ability to damage systems, information, and infrastructure. Existing InT research studie…
Safeguarding Virtual Healthcare: A Novel Attacker-Centric Model for Data Security and Privacy
Suvineetha Herath, Haywood Gelman, John Hastings +1
The rapid growth of remote healthcare delivery has introduced significant security and privacy risks to protected health information (PHI). Analysis of a comprehensive healthcare s…