Go to:
Logótipo
You are in:: Start > CC2009
Site map
FC6 - Departamento de Ciência de Computadores FC5 - Edifício Central FC4 - Departamento de Biologia FC3 - Departamento de Física e Astronomia e Departamento GAOT FC2 - Departamento de Química e Bioquímica FC1 - Departamento de Matemática

Security and Privacy

Code: CC2009     Acronym: CC2009     Level: 200

Keywords
Classification Keyword
OFICIAL Computer Science

Instance: 2021/2022 - 2S Ícone do Moodle

Active? Yes
Responsible unit: Department of Computer Science
Course/CS Responsible: Bachelor in Artificial Intelligence and Data Science

Cycles of Study/Courses

Acronym No. of Students Study Plan Curricular Years Credits UCN Credits ECTS Contact hours Total Time
L:CC 55 study plan from 2021/22 2 - 6 56 162
3
L:IACD 1 study plan from 2021/22 2 - 6 56 162

Teaching Staff - Responsibilities

Teacher Responsibility
João Paulo da Silva Machado Garcia Vilela

Teaching - Hours

Theoretical classes: 2,00
Laboratory Practice: 2,00
Type Teacher Classes Hour
Theoretical classes Totals 1 2,00
João Paulo da Silva Machado Garcia Vilela 2,00
Laboratory Practice Totals 2 4,00
João Paulo da Silva Machado Garcia Vilela 4,00
Mais informaçõesLast updated on 2022-02-25.

Fields changed: Calculation formula of final grade, Melhoria de classificação, Bibliografia Obrigatória, Componentes de Avaliação e Ocupação, Obtenção de frequência

Teaching language

Portuguese

Objectives

This course unit has the goal of providing students with an integrated perspective of the security and privacy fundamentals; it targets to endow students with the principles of IT security and data privacy.

Learning outcomes and competences

1. Understand the fundamental principles of system security and data privacy.
2. Identify vulnerabilities and threats to system security and privacy of data
3. Acquire skills on cryptography and its applications for system security.
4. Understand data protection regulations, and the impact of its requirements on security and privacy.
5. Select and apply privacy-enhancing technologies, as well as methodologies for risk assessment.

Working method

Presencial

Program

1. Principles of computer security: confidentiality, integrity, availability; concepts of risk, threats, vulnerabilities, attack vectors, security mechanisms;
2. Basic cryptography concepts: symmetric and public-key cryptography; encryption and authentication; data integrity, non-repudiation;
3. Cryptographic applications, including: secure storage and transmission of data;
4. Data privacy regulations and requirements;
5. Privacy threats and vulnerabilities, including: correlation and linkage attacks;
6. Privacy impact assessment and data management planning;
7. Anonymization and pseudonymization algorithms, re-identification risk assessment;
8. Secure multiparty computation and application to private data mining.

Mandatory literature

William Stallings; Computer security. ISBN: 1-292-22061-9
William Stallings; Information privacy engineering and privacy by design. ISBN: 978-0-13-530215-6
Matt Bishop; Introduction to computer security. ISBN: 0-321-24744-2
William Stallings; Cryptography and network security. ISBN: 9780138690175
Mark Stamp; Information security. ISBN: 9780470626399

Teaching methods and learning activities

The lectures are based on oral presentations, complemented with detailed examples and discussion of case-studies. Throughout the semester, the case-studies will be used to consolidate the exposed concepts, particularly by exercising security and privacy skills in data management through real-world scenarios.
Lab classes will consist on applying the introduced concepts through technological practice aiming at technical expertise in the application of security and privacy methodologies.

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation Weight (%)
Exame 60,00
Trabalho prático ou de projeto 40,00
Total: 100,00

Amount of time allocated to each course unit

designation Time (hours)
Elaboração de projeto 50,00
Estudo autónomo 56,00
Frequência das aulas 56,00
Total: 162,00

Eligibility for exams

Minimum grade of 35% on the total value of lab assignments.

Calculation formula of final grade

If ET < 35%: CF = RFC (not approved)
If ET >=35%: CF = 0,4 TR + 0,6 ET

where CF is the final classification, TR is the grade of the practical assignments and ET the grade of the final exam.

Special assessment (TE, DA, ...)

The same conditions as for regular students apply.

Classification improvement

The exam grade can be improved in the extra season (época de recurso).
The grade for the practical assignments holds for all exam seasons.
Recommend this page Top
Copyright 1996-2024 © Faculdade de Ciências da Universidade do Porto  I Terms and Conditions  I Acessibility  I Index A-Z  I Guest Book
Page created on: 2024-04-24 at 21:11:40 | Acceptable Use Policy | Data Protection Policy | Complaint Portal