SecureBioAI
Security and Safety of AI in Biotechnology: an interdisciplinary forum for AI security, cyberbiosecurity, healthcare security, Bio-LLM safety, and dual-use risk mitigation.
Securing AI-enabled biotechnology systems
AI, large language models, and foundation models are transforming genomic analysis, protein engineering, laboratory automation, drug discovery, biomedical diagnostics, and scientific decision support. These advances also introduce new cyberbiosecurity risks, including prompt injection, Bio-LLM jailbreaks, adversarial manipulation, biomedical data leakage, insider misuse, AI-enabled misinformation, and dual-use biological concerns.
Build a trusted interdisciplinary community
SecureBioAI brings together researchers, practitioners, policymakers, and educators working across cybersecurity, AI security, biotechnology, bioinformatics, healthcare security, and cyberbiosecurity to discuss technical, operational, and governance approaches for mitigating AI-related biological risks.
Important Dates
Topics of Interest
- Security and safety of bio-specialized LLMs and foundation models
- Adversarial attacks against biological AI systems
- Prompt injection and jailbreak techniques in Bio-LLMs
- AI-enabled biological threat modeling
- AI safety and alignment in biotechnology applications
- Secure genomic, biomedical, and healthcare data pipelines
- AI red-teaming methodologies for biotechnology systems
- Security of laboratory automation and biomanufacturing systems
- AI governance and dual-use risk mitigation
- Privacy-preserving AI for healthcare and biotechnology
- Secure deployment of AI-enabled healthcare systems
- Cyberbiosecurity education and workforce development
- AI-enabled insider threats in biotechnology environments
- Responsible disclosure and AI safety practices
- Security benchmarking and evaluation for Bio-LLMs
- Public policy, governance, and research security for biotechnology AI
Program Structure
Registration, Welcome Coffee, and Networking
Arrival, informal introductions, and preparation for the full-day workshop program.
Opening Remarks and Workshop Introduction
Overview of AI-enabled biotechnology ecosystems, emerging cyberbiosecurity and AI safety challenges, workshop goals, and expected outcomes.
Session 1: AI Security and Bio-LLMs
Security of biological foundation models, prompt injection and jailbreak attacks, adversarial ML, misuse, and dual-use concerns.
Morning Break
Coffee break and informal discussion.
Session 2: Cyberbiosecurity Infrastructure and Defense
Laboratory and biomanufacturing security, biomedical and genomic data protection, AI-enabled healthcare system security, and threat modeling.
Lunch and Networking
Extended lunch break to support networking and interdisciplinary discussion among participants.
Session 3: Applied AI Red-Teaming and Adversarial Exercises
Bio-LLM adversarial testing, AI safety evaluation frameworks, secure deployment strategies, practical demonstrations, and case studies.
Afternoon Break
Refreshment break and networking.
Session 4: Governance, Policy, and Research Security
Institutional governance frameworks, risk mitigation strategies, responsible AI deployment, national security, and international policy.
Session 5: Community Building and Future Directions
Open research challenges, benchmarking initiatives, workforce development, future collaborations, and workshop sustainability.
Workshop Organizers
Dr. Mohammad GhasemiGol
General Chair
Associate Professor, School of Cybersecurity, Old Dominion University
Dr. Daniel Takabi
Co-Chair
Professor & Director, School of Cybersecurity, Old Dominion University
Place organizer headshots in the images/ folder using these filenames: mohammad.jpg, takabi.jpg, potter.jpg, and palmer.jpg.