Adversarial BioAI Security (ABAS)

Adversarial BioAI Security (ABAS) explores the emerging risks and security challenges at the intersection of synthetic biology and generative AI. This program focuses on how AI models like GPT are used in CRISPR design, synthetic gene creation, and predictive pandemic modeling. Participants will learn about biofirewalls, dual-use research concerns, and governance frameworks for BioAI. With rising dual-use threats and the blending of AI with biotechnology, this course prepares professionals to recognize, assess, and manage bio-cyber risks in research and development.

Audience:

• Biosecurity professionals
• AI researchers and developers
• Biotechnology scientists
• Risk and compliance officers
• Government and defense analysts
• Policy and ethics specialists

Learning Objectives:

• Understand the risks of using AI in synthetic biology
• Explore adversarial threats in BioAI applications
• Learn governance and compliance frameworks for dual-use tech
• Analyze the role of LLMs in biological design and modeling
• Apply biosecurity best practices in AI-biotech convergence

Program Modules:

Module 1: Foundations of Adversarial BioAI Security

• Introduction to BioAI and synthetic biology
• GPT-style models in biological data processing
• Dual-use biotechnology overview
• Security implications of generative AI in life sciences
• Case studies on AI-driven bio-design
• Risk classification in BioAI systems

Module 2: CRISPR, Gene Editing, and AI Integration

• AI-generated CRISPR designs and efficiency
• Risks of automated genome modifications
• Adversarial misuse of gene editing tools
• Secure data handling in gene design
• Design constraints and validation protocols
• Ethical boundaries and oversight needs

Module 3: Synthetic Organisms and AI-Enabled Pathogens

• AI role in virus synthesis and sequence design
• DNA printers and potential misuse scenarios
• Predicting pathogen traits with machine learning
• Containment policies and digital safeguards
• Responsible innovation in synthetic biology
• Detection and interception of rogue designs

Module 4: Biofirewalls and Secure DNA Screening

• Biofirewall architectures and principles
• Tools for screening synthetic DNA requests
• Machine learning in anomaly detection
• Secure genomic data pipelines
• Industry standards and policy gaps
• Case analysis of real-world DNA misuse

Module 5: Pandemic Modeling and LLM Misuse

• How LLMs simulate outbreak scenarios
• Bias and misinformation in model outputs
• Forecasting accuracy vs. security risk
• Adversarial prompts and biological simulations
• Guidelines for responsible model deployment
• Collaboration between AI and public health sectors

Module 6: Dual-Use Governance and Risk Mitigation

• International frameworks and biosecurity treaties
• Oversight strategies for BioAI projects
• Legal and regulatory perspectives
• Organizational risk governance models
• Policy-making in fast-evolving AI-biotech
• Cross-sector coordination for security readiness

Exam Domains:

1. BioAI Threat Landscape and Risk Types
2. Synthetic Biology and Generative AI Convergence
3. Governance, Policy, and Legal Structures
4. Dual-Use Ethics and Risk Mitigation
5. Secure Data and Biofirewall Technologies
6. AI-Driven Biological Forecasting and Misuse Scenarios

Course Delivery:

The course is delivered through a combination of lectures, interactive discussions, and expert-led workshops, facilitated by professionals in BioAI security. Participants access online resources including readings, case examples, and guided analysis tools.

Assessment and Certification:

Participants will be assessed through quizzes, assignments, and a final project. Upon successful completion, participants receive a certificate in Adversarial BioAI Security (ABAS).

Question Types:

• Multiple Choice Questions (MCQs)
• True/False Statements
• Scenario-based Questions
• Fill in the Blank Questions
• Matching Questions (Matching concepts or terms with definitions)
• Short Answer Questions

Passing Criteria:

To pass the Adversarial BioAI Security (ABAS) Certification Training exam, candidates must achieve a score of 70% or higher.

Join the Tonex ABAS Certification Program to lead in securing the future of bio-AI convergence. Learn how to detect, prevent, and govern next-gen biotech threats.