IDENTIFYING DATA 2019_20
Subject (*) PRIVACY PROTECTION Code 17685107
Study programme
Computer Security Engineering and Artificial Intelligence (2016)
 Cycle 2nd
Descriptors Credits Type Year Period
4.5 Compulsory First 2Q
Language
Anglès
Department Computer Engineering and Mathematics
Coordinator
DOMINGO FERRER, JOSEP
 E-mail josep.domingo@urv.cat
Lecturers
DOMINGO FERRER, JOSEP
Web http://http://crises-deim.urv.cat/privprot
General description and relevant information Learn the basics of privacy, its legal principles and major design strategies . Gain expertise in database privacy and data anonymization.

Competences
Type A Code Competences Specific
 A1 Integrate the fundamental technology, applications, services and systems of Computer Security and Artificial Intelligence,in a broader, multidisciplinary context.
 A3 Understand and know how to apply the functioning and organisation of the Internet, the technology and protocols of new-generation networks, the models of components, intermediate software and services.
 A4 Design, develop, manage and evaluate mechanisms to certify and guarantee security in handling information and access to it in a local or distributed processing system.
 A5 Analyse the information needs considered in an environment and execute all stages of the construction process of a secure information system.
 G1 Project, calculate and design products, processes and installations in the areas of Computer Security and Artificial Intelligence
 G2 Perform mathematical modelling, calculation and simulation in company technology and engineering centres, particularly in tasks of research, development and innovation in the areas of Computer Security and Artificial Intelligence
Type B Code Competences Transversal
 CT2 Forming opinions on the basis of the efficient management and use of information
 CT3 Solve complex problems critically, creatively and innovatively in multidisciplinary contexts.
 CT4 Work in multidisciplinary teams and in complex contexts.
 CT7 Apply ethical principles and social responsibility as a citizen and a professional.
Type C Code Competences Nuclear

Learning outcomes
Type A Code Learning outcomes
 A1 Analyse the problems and their causes from a global focus in the medium and long term.
 A3 Design network protocols and private services for computer and telematic applications.
 A4 Design technology to guarantee privacy for scenarios of IT and telematics applications.
 A5 Identify the components of a decision-making problem and know how to decide the most suitable decision-making model.
 G1 Integrate theoretical knowledge into the realities to which it may apply.
 G2 Apply the techniques learned in a specific context.
Type B Code Learning outcomes
 CT2 Manage information and knowledge by making efficient use of the information technologies.
 CT3 Recognise the situation as a problem in a multidisciplinary, research or professional environment, and take an active part in finding a solution.
 CT4 Participate in the group in a good working environment and help to solve problems.
 CT7 Apply ethical and socially responsible principles as a citizen and a professional.
Type C Code Learning outcomes

Contents
Topic Sub-topic
1. Introduction a. Basic concepts of privacy
b. Legal principles
c. Privacy by design
d. Design strategies for privacy
2. Data privacy techniques a. Authentication
b. Attribute-based Credentials.
c. Secure and private communications
d. Anonymity and pseudo-anonymity in communications.
e. Privacy in data storages
f. Privacy-preserving computations.
g. Techniques for improving transparency.
h. Intervenability-enhancing techniques
3. Privacy in data bases a. Owner's privacy del propietari (Privacy-preserving data mining).
b. User's privacy (private information retrieval).
c. Respondent's privacy (anonymization).
4. User's privacy a. Issues of private information retrieval (PIR).
b. Modifications to PIR based on single users.
c. Modifications to PIR based on p2p networks (P2P PIR).
d. Rational behaviour in P2P PIR.
5. Anonymization in data bases a. Basic concepts
b. Privacy models
c. Protection of tables
d. Protection of interactive data bases.
e. Protection of microdata
g. Evaluation of statistical disclosure control methods.
h. Anonymizing software

Planning
Methodologies  ::  Tests
  Competences (*) Class hours
 Hours outside the classroom
 (**) Total hours
Introductory activities
A3
 1 1.5 2.5
Lecture
A1
A3
CT7
 26 38.5 64.5
Presentations / oral communications
A3
 1 1.5 2.5
Problem solving, exercises in the classroom
A1
G1
G2
CT3
CT4
 4 6 10
IT-based practicals
A3
A4
A5
CT3
CT4
 10 15 25
Personal attention
A3
 1 0 1
 
 
(*) On e-learning, hours of virtual attendance of the teacher.
(**) The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.

Methodologies
Methodologies
  Description
Introductory activities Difusió de l'actualitat sobre privadesa reflectida als mitjans
Lecture Sessions de teoria
Presentations / oral communications Presentacions a l'aula per part de grups de 2 o 3 alumnes de temes especialitzats concrets que els encarrega el professor.
Problem solving, exercises in the classroom Resolució a l'aula per part de grups de 2 o 3 alumnes de problemes relacionats amb cada tema.
IT-based practicals Implementació d'una tecnologia de preservació de la privadesa per part de cada grup de 2 o 3 alumnes.
Personal attention Atenció al despatx prèvia visita concertada

Personalized attention
Description
Students can request personal interviews with the teach as soon as they wish.

Assessment
Methodologies Competences Description Weight        
Presentations / oral communications
A3
 Presentations in the classroom by groups of 2 or 3 students on specialized subjects proposed by the teacher. 15%
Problem solving, exercises in the classroom
A1
G1
G2
CT3
CT4
 Problem resolution in the classroom by groups of 2 or 3 students. 5%
IT-based practicals
A3
A4
A5
CT3
CT4
 Implementation of a privacy-enhancing technology by each group of 2 or 3 students. 20%
Others  

Individual exam

60%
 
Other comments and second exam session

Sources of information

Basic

o   G. D’Acquisto, J. Domingo-Ferrer, P. Kikiras, V. Torra, Y.-A. De Montjoye i A. Bourka (2015) Privacy by Design in Big Data – An overview of privacy enhancing technologies in the era of big data analytics, European Union Agency for Network and Information Security-ENISA.

o   G. Danezis, J. Domingo-Ferrer, M. Hansen, J.-H. Hoepman, D. Le Métayer, R. Tirtea i S. Schiffner (2015) Privacy and Data Protection by Design: From Policy to Engineering, European Union Agency for Network and Information Security-ENISA.

o   J. Domingo-Ferrer, D. Sánchez i J. Soria-Comas (2016) Database Anonymization: Privacy Models, Data Utility and Microaggregation-Based Inter-Model Connections, Morgan & Claypool.

o   A. Hundepool, J. Domingo-Ferrer, L. Franconi, S. Giessing, E. Schulte-Nordholt, K. Spicer i P.-P. de Wolf (2012) Statistical Disclosure Control, Wiley.
Complementary

Recommendations
(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.