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План на курса
Introduction to Secure Agent Systems
- Security risks in multi-agent systems
- Overview of CrewAI security capabilities
- Compliance concerns in AI-driven workflows
Agent Identity and Authentication
- Managing identities and roles
- Secure communication between agents
- Token-based authentication and OAuth integration
Data Privacy and Confidentiality
- Data minimization and anonymization
- Secure data exchange between agents
- Encrypting sensitive inputs and outputs
Governance and Audit Logging
- Audit trails for agent actions
- Centralized logging and monitoring strategies
- Enforcing governance policies across agents
Policy Enforcement and Compliance Frameworks
- Aligning with industry compliance standards (e.g., GDPR, SOC 2)
- Custom policy engines and compliance guards
- Dynamic rules and policy-based decision making
Design Patterns for Secure Agent Collaboration
- Event-driven task orchestration
- Isolation of agent responsibilities
- Fault tolerance and incident response strategies
Deployment and Monitoring at Scale
- Security in CI/CD pipelines
- Containerized deployment with Docker and Kubernetes
- Monitoring compliance violations in real-time
Summary and Next Steps
Изисквания
- Experience with Python programming
- An understanding of agent-based systems
- Familiarity with cybersecurity and compliance principles
Audience
- Security specialists
- Enterprise AI leads
- Compliance officers
14 Часа
