This new course will be offered from October 2021 to June 2022. It is aimed at industrial participants and PhD students with an interest in one or more topics. Below are descriptions of the 11 modules to be offered in the first round. (The Autumn 2021 modules are shown in red.) To register for a module, please email firstname.lastname@example.org in the first instance.
Module A: Trustworthiness and Dependability in Edge-based CPS (key areas: Safety, Security, Predictability)
Timing: Jan – Mar 2022
Content: An overview of established views and definitions; relationships between concepts; trends; “schools”.
Module B: Fundamentals of Bayesian Inference using Probabilistic Programming (key areas: Safety)
Timing: Jan – Mar 2022
Content: *Basics of bayesian inference (SMC, MCMC); *Bayes rule, probabilistic modeling; *Using probabilistic programming to solve Bayesian probabilistic problems. Given through interactive lectures, hands-on exercises and take home exercises.
Module C: Safety Awareness Training (key area: Safety)
Timing: Oct – Dec 2021
Content: *Why you need to develop safe products (- Liability); *Prove your innocence (- Follow safety standards); *Legal significance of standards (- Engineers cannot hide from faults causing accidents); *What is functional safety? (- Computer control systems: A story of faults) (- Why is it so difficult to build safe and reliable computer control systems? Fundamental limits) (- Functional safety terminology) (- Safety planning: How to set up a successful “safe” development process; How to set up a successful “safe” organization); *Roles and responsibilities (- How can you prove you are innocent with respect to liability by developing and maintaining your product in as safe way?) (- Challenges when developing safety-related control systems); *The functional safety workflow (- Risk classification) (- Root cause analysis) (- Diagnostics and safe design) (- Architecture selection) (- Verification and test) (- Compiling the safety case; proving your innocence) (- Safe system development according to ISO26262/ISO13849/EN50128; will also mention other standards); *Software development according to standards); *Recap and conclusion
Module D: Fundamentals of Security for Edge Computing (key area: Security)
Timing: Oct – Dec 2022 (if there is strong interest, this could possibly also be offered Oct – Dec 2021, tbc)
Content: *Introduction to cryptography (secret and public cryptosystems, encryption and authentication basics); *Attack vectors; *Anti-tamper techniques.
Module E: ML Security and Privacy (key areas: Security)
Timing: Apr-June or Oct-Dec 2022 (tba)
Content: *Taxonomy of attacks on ML; *Adversarial attacks on classification; *ML fingerprinting and watermarking; *Definitions of privacy; *Approaches to privacy preserving learning.
Module F: Industry Security Challenges in Cloud Deployments (key area: Security)
Timing: Nov 2021
Content: To highlight problems and identify research opportunities: *Introduction (Threat model in cloud, ideal wanted position); *Solution with TEEs (Trusted Execution Environment) and short-term challenges; *Potential residual threats (e.g. side channel attacks, trust in HW vendors).
Module G: 5G Security Standardization in 3GPP (key area: Security)
Timing: Oct 2021
Content: A sneak peek into how 3GPP – the defacto standardization organization for all Gs – works in general. Then, we will describe the most important security and privacy features that were introduced in 5G, making 5G the most trustworthy mobile network generation ever.
Module H: Multi-agent Decision Making (key area: Predictability)
Timing: Jan-Mar 2022 or Oct-Dec 2022
Content: *Game theory fundamentals; *Models of learning; *Emergence of equilibria.
Module I: Industrial, Reliable Wireless Networking – Fundamentals and Systems (key area: Predictability)
Timing: Mar – Apr 2022
Content: *Underlying principles; *Communication theory background; *Implementation principles; *Examples (iWLAN, IO-Link, 5G, 802.11be)
Module J: Machine Reasoning Explainability (an AAMAS tutorial) (key area: Predictability)
Timing: Jan-Mar 2022
Content: *Concept; *Technical Part 1(Inference-Based Explanations; SAT/SMT Analysis of Inconsistencies; Argumentation-Based Explanations); *Technical Part 2 (Explainable Planning; Symbolic RL, Explainability; Causal Approaches to Explainability); *Conclusions
Module K: Programming Python AI study circle (key area: Predictability)
Timing: Apr-June 2022
Content: Learn Python programming skills