Logo

Data Privacy and Security

Code: 104369
Credits: 6
2026/2027
Degree programme Type Course
Data Engineering OP 4

Contact lecturer

Name :
Guillermo Navarro Arribas
Email :
guillermo.navarro@uab.cat

Teaching staff

Julián Salas Piñón

Group languages

You can consult this information at the end of the document.

Prerequisites

In this subject, we will make use of knowledge acquired during the degree. There is no mandatory requirement, but it will be assumed that students have a base knowledge of statistics, cryptography, graphs, programming, and computer networks.

Objectives

The objectives of the subject are:

  • Understand the issue of privacy in digital environments.
  • Knowledge of tools that provide privacy to various levels.
  • Understand the main models of data privacy.
  • Understand and know mechanisms for data evaluation and protection.
  • Get to know some advanced mechanisms for privacy.
  • Knowledge of mechanisms for private communication.

Learning outcomes

  1. Work cooperatively in complex and uncertain environments and with limited resources in a multidisciplinary context, assuming and respecting the role of the different members of the group.
  2. Demonstrate sensitivity towards ethical, social and environmental topics.
  3. Students must develop the necessary learning skills to undertake further training with a high degree of autonomy.

Contents

  • Introduction to privacy
  • Data privacy
  • Models: k-anonymity, differential privacy
  • Data privacy protection methods
  • Private communications
  • Privacy and machine learning

Learning activities and methodology

Title Hours ECTS Learning outcomes
Preparation of practical sessions 25 1
Tutorials 10 0.4
Practical sessions 25 1
Theoretical sessions 25 1
Preparation of theoretical sessions 37.5 1.5

The subject is taught in two-hour sessions. These sessions will be organized dynamically and will require the active participation of the students. Throughout the course there will be sessions of more theoretical typology and another of practical typology.

Theoretical sessions can be structured in various ways. In some cases, the teaching staff, prior to the session, will make available to the students material on the topic to be discussed. In accordance with this material, different types of sessions will be structured. For example, question and answer sessions where the students will formulate the doubts that have arisen from the previous work on the material provided. In these sessions, the teaching staff will also challenge the students to bring out the most relevant aspects of the material being worked on. There will also be sessions where the students, in groups, will present a more detailed study of some of the topics covered in the subject. Depending on the specific topic to be dealt with, the theory session can also be structured as a master class.

The practical type sessions include the resolution of questions or exercises, such as the resolution of more technical tasks of a practical type.

 

Annotation: within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.

Assessment

Continuous assessment activities

Title Weight Hours ECTS Learning outcomes
Practical activities 50 12.5 0.5 1, 2, 3
Topic presentation and preparation 10 1 0.04 1, 2, 3
Evaluation in lecture sessions 40 14 0.56 3

Final assessment and grading: The final grade is calculated by weighting the assessment activities as follows:

  • In-class assessment: assessment of the knowledge acquired in class. This will take the form of individual exercises or theoretical tests during class sessions. Weight: 40%
  • Practical assignments: completion of practical assignments or projects in groups, with an individual assessment test. Weight: 50%
  • Topic preparation and presentation: preparation of a topic related to the course, to be presented in class. Weight: 10%


The in-class assessment component requires a minimum average grade of 5. If this is not reached, a final exam covering the entire course may be taken.


The practical assignments each require a minimum grade of 4.0. If a practical is not passed, it may be resat at the end of the course.


The topic presentation does not require a minimum grade and cannot be resat.


Students who reach the minimum number of points needed to pass the course, but have not reached the minimum grade in one of the assessment activities, will be given a final grade of 4.5.


The grade "not assessable" will be given to students who do not participate in any of the assessment activities.


For each assessment activity, a location, date, and time for review will be indicated, during which students may review the activity with the teaching staff. In this context, complaints about the grade of the activity may be submitted, which will be evaluated by the teaching staff responsible for the course. If a student does not attend this review, the activity will not be reviewed afterward.


Awarding of honors (Matrícula de Honor): honors may only be awarded to students who have obtained a final grade equal to or higher than 9.00. Up to 5% of enrolled students may receive honors.


Activity schedule: Dates for continuous assessment and submission of assignments and practicals will be published on the virtual campus and may be subject to scheduling changes to accommodate possible incidents. Any such changes will always be announced on the virtual campus, as this is understood to be the standard channel of communication between teaching staff and students. Likewise, assessment mechanisms, methodology, or general operation of the course not specified in this guide will be detailed with sufficient advance notice.


Partial credit transfer for repeating students: Initially, there is no plan to allow credit transfer for parts of the course, nor special tests for repeating students. However, this may be reconsidered at the start of the course depending on the content of each part.


Ethical commitment: Without prejudice to other disciplinary measures deemed appropriate, and in accordance with current academic regulations, irregularities committed by a student that could lead to a change in the grade of an assessable activity will be graded with a zero (0). Assessment activities graded in this way through this procedure cannot be resat. If passing any of these assessment activities is required to pass the course, the course will be failed outright, with no opportunity to resit it in the same academic year. These irregularities include, among others: copying, in whole or in part, a practical, report, or any other assessment activity; allowing someone to copy from you; submitting group work not carried out entirely by the group members (this applies to all members, not only those who did not contribute); unauthorized use of AI (e.g., Copilot, ChatGPT, or equivalents) to solve exercises, practicals, and/or any other assessable activity; presenting as one's own material produced by a third party, even if translated or adapted, and in general submitting work with elements that are not original and exclusive to the student; having communication devices (such as mobile phones, smartwatches, camera pens, etc.) accessible during assessment tests; talking to classmates during assessment tests; copying or attempting to copy from other students during assessment tests; using or attempting to use subject-related written materials during assessment tests when these have not been explicitly authorized.


The numerical grade on the transcript will be the lower of 3.0 or the weighted average of the grades if the student has committed irregularities in an assessment activity (and, therefore, a passing grade through compensation will not be possible). In future editions of this course, students who have committed irregularities in an assessment activity will not be granted credit transfer for any assessment activities already completed. In summary: copying, allowing copying, or plagiarizing (or attempting to do so) in any assessment activity results in a FAIL, non-compensable, with no credit transfer for parts of the course in subsequent years.


For this course, the use of artificial intelligence (AI) technologies is permitted exclusively for support tasks, such as bibliographic or information searches, text correction, or translations. Students must clearly identify which parts have been generated using this technology, specify the tools used, and include a critical reflection on how these have influenced the process and final result of the activity. Lack of transparency regarding AI use in assessable activities will be considered a breach of academic integrity and may result in a partial or total penalty on the activity's grade, or more severe sanctions in serious cases.


Single assessment (Avaluació única): This course does not offer the single assessment option.

Bibliography

Given the dynamism of the subject, many bibliographic references and material will be provided during the course. Here are some more generic references:

  • Vicenç Torra (2022) Guide to data privacy : models, technologies, solutions. Springer. https://bibcercador.uab.cat/permalink/34CSUC_UAB/1fbc57r/alma991010721333006709
  • Cynthia Dwork, Aaron Roth (2014) The Algorithmic Foundations of Differential Privacy. Foundations and Trends in Theoretical Computer Science, https://www.cis.upenn.edu/~aaroth/Papers/privacybook.pdf.
  • Solon Barocas, Moritz Hardt, Arvind Narayanan (2009) Fairness and Machine Learning. https://fairmlbook.org/
  • Anthony D. Joseph, Blaine Nelson, Benjamin I. P. Rubinstein, J. D. Tygar (2019) Adversarial Machine Learning. Cambridge University Press. https://bibcercador.uab.cat/permalink/34CSUC_UAB/1fbc57r/alma991010753943706709
  • Christof Paar, Pelzl Jan. (2010) Understanding Cryptography: A Textbook for Students and Practitioners. Springer Berlin Heidelberg, 2010. https://bibcercador.uab.cat/permalink/34CSUC_UAB/1fbc57r/alma991010489805006709

Software

Given the multidisciplinary nature of this subject, we will use different tools and programming languages depending on the specific activity to be carried out, both for the labs and for the activities and exercises.

Course groups and languages

The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE

Type of teaching Group Language Semester Shift
(PAUL) Classroom practices 81 Catalan/Spanish first semester morning-mixed