This paper introduces Athena, a novel impact analysis approach that combines dependence graph information with conceptual coupling using deep representation learning.

The paper introduces a comprehensive framework, Realtime Risk Studio, that operationalizes qualitative risk models (Bowtie diagrams) into formal, probabilistic, and intervention-ready runtime models u…

The paper proposes MVRAF, a data-driven framework that quantifies vulnerability risk in large-scale cloud infrastructure by integrating multiple attack attributes and analyzing cumulative risk distrib…

This paper provides the first comprehensive threat model for IoT-enabled Controlled Environment Agriculture (CEA) systems, identifying 123 unique threats and proposing a defense-in-depth framework to…

This study analyzed the online exposure of Thai National Identification Numbers and other sensitive personal data, revealing over 1.2 million records, primarily originating from government websites, w…

The paper proposes an LLM-enhanced methodology using RAG to automate the creation of security profiles, ensuring compliance with Ukrainian cybersecurity regulations and international best practices.

The paper analyzes a large dataset of JavaScript packages to demonstrate that a small number of vulnerable dependencies can propagate vulnerabilities across a disproportionately large number of packag…

This ethnographic study examines how professional music producers use AI and automated tools, finding that the tension between the need for speed and maintaining creative control is a key area for fut…

This paper investigates ways to transform a theory-based methodology for optimizing visual analytics workflows from theory to practice using case studies.

This paper explores the causes of inconsistent vulnerability scanner findings in the open-source ecosystem.

The BEAMS initiative establishes comprehensive benchmarks and evaluates AI tools for modeling and simulation, finding that current AI tools excel at qualitative discussion tasks but struggle with comp…

This paper presents an empirical investigation on the distribution, evolution, and maintenance implications of Domain-Driven Design (DDD) building blocks in open-source GitHub repositories.

The paper introduces EduMPI, a learning support tool for simplifying cluster usage and performance analysis of MPI parallel programs for students.

This paper proposes a game-theoretic framework using Shapley Effects and Pareto front sets for interpretable hyperparameter-objective interaction analysis.

This paper introduces HarmAmp, a new benchmark for multi-turn harm amplification, and proposes TrajSafe, a proactive monitoring system that significantly reduces harmfulness in LLM interactions while…

This paper provides the first large-scale characterisation of Domain-Driven Design (DDD) adoption and implementation on GitHub.

This paper compares and analyzes contribution policies of six open-source organizations towards governing AI-driven incidents in their projects, deriving a six-dimensional taxonomy and identifying gap…