PET: PRIVACY ENHANCING TECHNOLOGIES - 2023/4

Module code: COM3030

Module Overview

This module introduces general concepts of privacy enhancing technologies and aligns with key concepts recommended by the CyBoK. It will motivate the need for privacy in the modern world and touch on legal considerations, introduce concepts of transparency, control and confidentiality for privacy, and look at privacy preserving and democratic values. This module will also explore how these are realised in a range of applications.

Module provider

Computer Science and Electronic Eng

Module Leader

DRAGAN Catalin (CS & EE)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 6

Module cap (Maximum number of students): 200

Overall student workload

Independent Learning Hours: 80

Lecture Hours: 22

Laboratory Hours: 20

Guided Learning: 6

Captured Content: 22

Module Availability

Semester 1

Prerequisites / Co-requisites

COM2041 Computer Security A

Module content

Indicative content includes:
¿ Need for privacy
¿ Legal aspects (e.g., GDPR, Data Protection Act)
¿ Privacy as transparency and control (e.g., policy settings, policy negotiations and integration, access control, consent forms)
¿ Privacy and democratic values (e.g., anonymous petitions, e-voting systems and their properties)
¿ Privacy as confidentiality (e.g., metadata confidentiality, data confidentiality, protecting data in transit, protecting data during processing, verification in the encrypted domain)
¿ Privacy-preserving applications (e.g., privacy-preserving machine learning, federated learning)

Assessment pattern

Assessment type Unit of assessment Weighting
School-timetabled exam/test Class Test (2 hours) 40
Examination Closed Book 2 hour Exam 60

Alternative Assessment

No alternative assessment available

Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate they achieved the learning outcomes. The summative assessment for this module consists of one class test addressing theoretical concepts and one closed book exam addressing all learning outcomes. For formative assessment and feedback, the students will have weekly formative tests and solutions to all lab/seminar exercises and activities.

Module aims

  • Introduce students to concepts of privacy for transparency, control, and confidentiality.
  • Develop an understanding of how privacy is achieved in practice.
  • Develop practical experience and familiarity with privacy-preserving tools.

Learning outcomes

Attributes Developed
001 Understand privacy principles in theory and practice CK
002 Understand diverse range of privacy-preserving methods CKT
003 Experience with practical applications of privacy-preserving techniques KPT
004 Describe current trends in privacy technologies and applications T

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Methods of Teaching / Learning

The learning and teaching strategy is designed to encourage a wide understanding of privacy concepts, from principal foundations to practical applications, by delivering a course that develops analytic and practical skills. It is designed to:

¿ Help students develop a core understanding of privacy principles
¿ Explain common techniques to achieve privacy
¿ Enable students to apply knowledge to practical applications

The module will have 22 hours (11 x 2hrs) of face-to-face lectures, which will primary delivery for the module content.

There will be 20 hours (10 x 2hrs) of labs that will allow the students to apply knowledge learnt in the lecture. They will also learn to use privacy-preserving tools.

The students will also undertake independent study (86 hours) to reinforce understanding of the module content and lab sessions. It will allow time to read supporting textbooks, work through any additional exercises, prepare for the class test and complete the coursework.

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: COM3030

Other information

Digital Capabilities Computer Security is vital to all aspects of life and this module teaches both theory and practical skills to secure a system. These skills are now fundamental to developing solutions to problems as a computer scientist. Network systems are a part of most industries and the skills learned in this module will give students the knowledge to secure these systems Employability This module provides security, cryptographic theory and software skills that are vital in today¿s industry. Students are equipped with theory practical problem-solving skills that allow them to work with and reason about security in computer and networked systems. These skills are highly valuable to employers. Cyber Security experts are highly sought-after. Global and Cultural Skills Computer Science is a global language and the tools and languages used on this module can be used internationally. This module allows students to develop skills that will allow them to reason about and develop applications with global reach and collaborate with their peers around the world. Resourcefulness and Resilience This module involves practical problem-solving skills that teach a student how to reason about security in complex hardware and software systems through combining the foundation theory taught with practical technologies for systems that are in everyday use.

Programmes this module appears in

Programme Semester Classification Qualifying conditions
Computing and Information Technology BSc (Hons) 1 Optional A weighted aggregate mark of 40% is required to pass the module
Computer Science BSc (Hons) 1 Optional A weighted aggregate mark of 40% is required to pass the module

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2023/4 academic year.