Hours:
16 hours (4 credits)

Room:

Meeting Room, Dept. of Information Engineering, Largo Lazzarino 1, Pisa, Sixth Floor

To register to the course, click here

Short Abstract:

Cyber-Physical Systems (CPS), comprising Internet of Things (IoT), have a wide variety of applicationsCyber-Physical Systems (CPS), comprising Internet of Things (IoT), have a wide variety of applicationsto smart environments, such as smart grid, smart transportation, smart water distribution networks,smart manufacturing, smart healthcare, and smart agriculture. The aim is to improve human qualityof life and make the society a safer place to live in. However, smart living CPS and IoT domains arevulnerable to a wide variety of unsafe events, threats, adversarial attacks (e.g., false data injection,data poisoning or evasion, deliberate data manipulation or perturbation). Detecting and interpretingsuch threats in real time is vital to proactively respond to the underlying cause and preventimmediate impacts on civilians and the economy. Threats manifest themselves as anomalies in thesensed time series data and machine learning model parameters, and can be formulated as ananomaly detection problem, where we first learn the underlying mathematical structure of benignbehavior and then detect anomalies as deviations from the learned structure.

This research-based Ph.D. course aims to cover a unified theory for detecting anomalies (threats) insmart living CPS in a lightweight, timely, and unsupervised manner. The approach is based on derivinginvariants and latent space that use time series data analytics, machine learning, information theory,and reputation scoring, and ecology models. The proposed unified theory will be validated using realworlddata collected from multiple CPS and IoT domains such as smart grid, smart transportation,and smart water networks. The course will be concluded with future research directions.

Course Contents in brief:

1. Sensors, IoT, CPS and UAV Networks
2. Smart Environments
3. Security Challenges in CPS
4. Machine Learning and Mathematical Models
5. Mobile Crowd Sensing
6. Securing Smart Living CPS
   1. Smart Grid
   2. Smart Transportation
   3. Smart Water Distribution
7. Smart Agriculture and Smart Healthcare
8. Conclusions and Open Problems

Schedule:

1. May 12 – 2:00-6:00 pm
2. May 13 – 10:30-12:30 am; 2:00-4:00 pm
3. May 14 – 10:30-12:30 am; 2:00-4:00 pm
4. May 15 – 10:30-12:30 am; 2:00-4:00 pm