Software Security & Privacy
Secure software design, vulnerability and privacy analysis, data protection, security testing, and evidence-based assurance.
Research
We study secure and trustworthy software through interconnected research in software security and privacy, AI, software analysis and quality, and empirical studies.
Our focus
Research areas
Mobile Security & Malware Analysis
Security and privacy of mobile ecosystems, including Android, malware detection and characterization, app repackaging, inter-app communication, and vulnerability analysis.
Trustworthy AI
Security, reliability, evidence grounding, and responsible evaluation of AI systems used in software and security contexts.
AI for Software Engineering
LLMs, coding agents, and intelligent automation for software generation, testing, debugging, analysis, repair, and secure development.
Software Analysis & Quality
Program and repository analysis, software metrics, maintainability, architecture, code smells, analytics, and security-aware quality assessment.
Empirical Software Engineering
Evidence-driven studies of software systems, developers, tools, datasets, and engineering practices using reproducible empirical methods.
Integrated themes
How the research areas connect
THEME 01
Software Security & Privacy
We investigate software security and privacy risks at code, architecture, application, and ecosystem levels. Current interests include mobile security, malware and vulnerability analysis, privacy risks, secure code analysis, and software assurance.
Connects:
Software Security & Privacy · Mobile Security & Malware Analysis
THEME 02
AI, Trust & Assurance
We study AI as both a software-engineering capability and a source of new assurance challenges. This includes trustworthy AI, LLMs and coding agents, security analysis with AI, evidence-grounded reasoning, validation, and false assurance.
Connects:
Trustworthy AI · AI for Software Engineering
THEME 03
Software Analysis & Empirical Studies
We use empirical methods and software analysis to understand software properties at scale, including metrics, quality, maintainability, architecture, software analytics, datasets, and reproducible evaluation.
Connects:
Software Analysis & Quality · Empirical Software Engineering
Research artifacts
Many NEXUS projects produce datasets, tools, benchmarks, and other reproducible resources to support follow-on research.