COURSE OUTLINE
Session 1
AI Building Blocks
- AI development lifecycle
- Data, model, applications
- Data Centres and Cloud platforms
Session 2
Data Centre fundamentals
- Datacenter internals
- Physical security
- Support subsystems
- Building management systems
Session 3
Network layer security
- Network segregation in DC
- Infiniband security
- Software Defined Network
Session 4
Bare metal management
- BMC, UEFI
- Vulnerabilities of OOB interfaces
- Security of ML/GPU servers
- Supply chain management
Session 6
Storage and noSQL databases
- Security of Storage, SAN/NAS
- Document and Graph databases
- NoSQL injections and other security issues
- PaaS and Serverless
Session 5
Virtualisation and Containers
- VM trust model
- Hypervisors security issues
- Docker security
Session 8
Cloud GRC
- Regulatory compliance
- Policy and procedures
- NoSQL injections and other security issues
- Security checklist
Session 7
Cloud management
- Cloud security model
- Cloud security features
- Orchestration and high-performance software (OpenStack, OpenHPC) security
Session 10
AI Implementation security
- Vulnerabilities in machine learning frameworks
- AI and AppSec
Session 9
AI as a product
- AI Applications Development Life Cycle
- AI Threat Model
- Secure SDL touchpoints
Session 12
AI and Privacy
- Data collection and privacy
- Model data extraction
- Black and gray box reverse engineering
Session 11
Model security
- Adversarial ML
- Scaling Attack
- Model backdoor
Session 14
AI for Cyber
- Defensive AI applications
- Offensive AI applications
- AI vs AI
Session 13
Industry-specific AI Security
- Geospatial
- Smart City
- Medical
Session 15
Test