Program Overview

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Introduction to Data Security

Course Description

The course aims to provide an introduction to and an overview of the concepts of vulnerability, threats, and mechanisms for securing data systems and networks.

Course Content

The course covers:

• Human, organizational, and regulatory aspects, including risk management, law and regulation, as well as human factors, privacy, and network etiquette
• Attacks and defense, including malware and attack technologies, detection and handling of security incidents, and investigation of incidents
• System security, including encryption, operating system and virtualization security, distributed system security, as well as authentication, authorization, and accountability
• Software and platform security, including software security, web and mobile security, secure software design and development
• Infrastructure security, including network security, hardware security, security for cyber-physical systems, and security in physical storage

Learning Outcomes

Upon completion of the course, students will have the following learning outcomes defined in knowledge, skills, and general competence:

Knowledge

• Describe typical threats to modern digital systems and outline techniques for defense against each threat
• Describe the foundation for modern cryptography
• Describe popular mechanisms and protocols for security in data systems and networks
• Be aware of the challenges in solving security problems

Skills

• Be able to acquire new security mechanisms in a short time
• Be able to discuss, informally and semi-formally, aspects of security, as described in the course, with partners
• Be able to identify security tasks that need to be handled by experts

General Competence

• Be familiar with new ideas and innovation processes
• Be able to exchange views with others with relevant background and participate in discussions on the development of good practice

Course Details

Full-time/Part-time

The course is offered full-time.

Credits and Scope

The course is worth 10 credits.

Study Level

The course is at the Bachelor level.

Teaching Semester

The course is taught in the autumn semester.

Language of Instruction

The language of instruction is English.

Resources

• Time schedule

Admission Requirements

Prior Knowledge

There are no prior knowledge requirements for the course.

Recommended Prior Knowledge

The following courses are recommended: INF100, MNF130, and MAT121. All courses can be taken in parallel.

Credit Reduction

There is no credit reduction for the course.

Admission Requirements

To start the course, there is a requirement for admission to the Faculty of Natural Sciences and Technology.

Teaching and Assessment Methods

Teaching Methods

• Lectures: 4 hours per week for 13 weeks
• Exercises: 2 hours per week

Mandatory Teaching Activities

Approved mandatory assignments. Mandatory activities are valid for two semesters: the semester they are approved and the following semester.

Assessment Methods

The course uses the following assessment methods:

• Digital written exam (3 hours)

Grading Scale

The grading scale used is A-F.

Examination Semester

There is an ordinary exam every semester. In semesters without teaching, the exam is held early in the semester.

Course Evaluation

Students will evaluate the teaching in accordance with the University's and the department's quality assurance system.

Administrative Responsibility

The Faculty of Natural Sciences and Technology, Department of Informatics, has administrative responsibility for the course and study program.