ACIT4280 Privacy by design Emneplan

Privacy by Design is a fundamental requirement of the General Data Protection Regulation (GDPR) for all systems operating on personal information. This course provides an introduction to privacy and data protection including the legislation such as the GDPR, privacy enhancing technologies, privacy management, designing for privacy, and privacy patterns in software design. It enables the students to understand regulation, to identify privacy risk and consequences of data breaches, introduces them to privacy controls and builds skills in their application in a structured privacy engineering process.

All aids are permitted, provided the rules for plagiarism and source referencing are complied with.

For the oral exam, students will only have access to the project report.

No formal requirements over and above the admission requirements.

Knowledge

On successful completion of this course the student has:

• knowledge of basic legal privacy concepts and data protection regulations and will be able to apply them in systems analysis and design
• knowledge of concepts of privacy by design and privacy impact assessment and the ability to compare different assessment methods
• applicable knowledge of principles of architectural tactics for privacy and privacy patterns.

Skills

On successful completion of this course the student can:

• map legal privacy principles to technical privacy concepts
• design and plan solutions that map security and privacy goals to mitigation mechanisms and technologies
• apply privacy by design and analyze software architectures using privacy impact assessments

• apply appropriate architectural tactics for privacy and privacy patterns in order to derive and create solutions that mitigate privacy risks

General competence

On successful completion of this course the student can:

• explain and apply their knowledge of security and privacy enhancing technologies

• Online course material for preparatory reading (flipped classroom approach)
• Bi-weekly lecture and case discussions
• Bi-weekly presentations of student home assignment cases

The following required coursework must be approved before the student can take the exam:

One group assignment (2-5 students appointed by teacher) consisting two parts: a report and a presentation.

Individual written digital exam, 3 hours. The exam result can be appealed.

New/postponed exam: In case of failed exam or legal absence, the student may apply for a new or postponed exam. New or postponed exams are offered within a reasonable time span following the regular exam. The student is responsible for registering for a new/postponed exam within the time limits set by OsloMet. The Regulations for new or postponed examinations are available in Regulations relating to studies and examinations at OsloMet.

A student who has completed this course should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

On successful completion of the course the student

• is familiar with fundamental key concepts within information theory such as Shannon Entropy, noiseless and noisy-channel coding theorems, and optimal coding algorithms.
• knows what a qubit is and how the information content grows when qubits are connected.
• is familiar with the elementary operations, or gates, of quantum computing - including gates such as the Hadamard gate and CNOT.
• knows the present state of the art when it comes to existing quantum computers.
• can implement simple quantum algorithms and run them on actual quantum computers.
• knows basic quantum communication protocols such as key distributions and secret sharing and understands the ideas behind them
• is familiar with several methods, such as Shor’s algorithm and quantum annealing, which enables quantum computers to solve problems considerably faster than classical computers.
• is familiar with how quantum technology affects traditional encryption schemes, and provides novel ones.

Skills

On successful completion of the course the student

• is able to model and simulate numerically simple quantum systems and processes - both on classical and quantum computers.can independently devise, implement and run calculations and simulations of simple quantum systems.
• can design her/his own quantum algorithms.

General competence

On successful completion of the course the student

• is familiar with several phenomena specific to quantum physics - such as quantization, particle interference, collapse of the wave function, particle spin, entanglement and decoherence - and how they may manifest themselves within quantum computing.
• is familiar with how information may be described by quantitative means - both within a classical and a quantum context.
• knows how to revise and improve on implementations of quantum programs.
• can address some of the practical challenges related to building quantum computers.
• knows the importance of quantum computing within information technology and the open challenges yet to be solved in this scope.

The teaching is organized in sessions where the subject material is presented, and in sessions where the students solve problems on their laptops and prototype quantum computers. The latter is done using online cloud platforms currently provided by enterprises such as, e.g., IBM and D-Wave. Between these sessions, the students are expected to work independently, using their computers, access to quantum computers, and course notes.

In the last stage of the course, the students are required to complete and present an individual project that involves (i) simulation of a quantum system/process, (ii) simulation of a quantum communications protocol, or (iii) creation of a quantum code and its implementation on a quantum processor using an online cloud platform. The project should be concluded by submitting a report which provides a description of the project, its motivation and implementation, and an analysis the obtained results.

None

The assessment will be based on a portfolio of the following:

• One individual project delivery consisting of a report (2000 - 4000 words)
• An individual oral examination (30 minutes)

The portfolio will be assessed as a whole and cannot be appealed.

New/postponed exam

In case of failed exam or legal absence, the student may apply for a new or postponed exam. New or postponed exams are offered within a reasonable time span following the regular exam. The student is responsible for registering for a new/postponed exam within the time limits set by OsloMet. The Regulations for new or postponed examinations are available in Regulations relating to studies and examinations at OsloMet.

In the event of a postponed examination in this course the exam may be held as an oral exam. Oral exams cannot be appealed.