DATA PROTECTION & PRIVACY
6 credits during the 2nd year of 10852 COMPUTER SCIENCE (LM-18) GENOVA
OVERVIEW
The course will introduce methodologies at the state of the art for protecting several data types (e.g., databases, time series, graphs, longitudinal data and transactional data). Furthermore, the course will provide some insights on legal aspects related to the protection of the user's privacy.
AIMS AND CONTENT
LEARNING OUTCOMES
Students will learn key elements in data protection and privacy: data privacy and anonymity, metrics and techniques; macro and microdata protection; data protection in outsourcing scenarios; privacy on the web; advanced access control.
AIMS AND LEARNING OUTCOMES
- To understand the data privacy problem
- To learn data anonymization algorithms at the stare of the art
- To read and understand a scientific paper
- To implement an anonymization technique, autonomously.
PREREQUISITES
- Programming
- Foundations of Algorithms and Data Structures
- Algebraic and statistical foundations.
Teaching methods
lectures + hands on
SYLLABUS/CONTENT
- Static Data Anonymization for Multidimensional Data and Complex Data Structures
-
Threats to Anonymized data
-
Privacy-preserving Test Data Manufacturing
-
Synthetic data generation
-
Dynamic Data Protection: Tokenization
-
Privacy through Data Hiding
-
Privacy Regulations
RECOMMENDED READING/BIBLIOGRAPHY
Scientific papers and slides that will be provided during the course
TEACHERS AND EXAM BOARD
Ricevimento: By appointment.
Exam Board
ALESSIO MERLO (President)
MARCO MARATEA
ALESSANDRO ARMANDO
LESSONS
Teaching methods
lectures + hands on
LESSONS START
October 2018
EXAMS
Exam description
Oral examination
Assessment methods
Pitch and demo of a project