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