Security and Privacy of Smart Environment

Overview

Smart environments (SEs) are transforming modern life by integrating advanced technologies to enhance urban living, healthcare, industrial processes, and home automation. These interconnected ecosystems leverage IoT devices and sensors to collect, analyze, and act on real-time data, fostering smarter cities, intelligent transportation systems, and energy-efficient buildings. However, smart environments' growing complexity and scale also introduce significant security and privacy challenges.

Smart environments often rely on heterogeneous devices and systems, many of which are resource-constrained and lack robust security mechanisms. This creates vulnerabilities that can be exploited for cyberattacks, including Distributed Denial-of-Service (DDoS) attacks, ransomware, data breaches, and unauthorized surveillance. The integration of cloud computing, artificial intelligence (AI), and big data analytics within smart environments further amplifies concerns about data privacy, regulatory compliance, and the ethical implications of extensive data collection and monitoring.

This class provides an in-depth exploration of security and privacy issues in smart environments, focusing on threat models, attack techniques, and defense strategies. Students will develop practical skills to assess and mitigate risks across interconnected systems and design secure, resilient smart infrastructures. Through hands-on exercises, real-world case studies, and exposure to the latest security trends, students will be prepared to address the unique challenges posed by smart environment security across various industries.

The course will discuss topics related to privacy and security in different domains, including:

-  Security of Internet of Things 

- Future Internet Technologies

- Machine Learning & security for SEs

- Extended reality

- Application scenarios (automotive, healthcare, space, underwater,  etc.)

General Information

• Student reception: The professors receive by appointment, to be taken via email.

• Any communication between teachers and students will be done through the classroom page of the course. You are therefore invited to register for it. Classroom code: TBD

Teaching Material

The teaching material will be available on the classroom page.

Lectures (I semester)

• Monday 16:00 - 19:00

• Wednesday 17:00 - 19:00

Location: room T1  (Building E) Viale Regina Elena 295

Previous academic years: