IMT4210 - Computational Forensics


Examination arrangement

Examination arrangement: Assignment (essay/project)
Grade: Letter grades

Evaluation Weighting Duration Grade deviation Examination aids
Assignment (essay/project) 100/100 ALLE

Course content

Deepening of knowledge and skills in computer-assisted digital investigations and forensics using specific methods to realistic case scenarios. Methods may include yet are not limited to:

-Forensic Statistics

-Forensics Data Science

-Pattern Recognition

-Machine Learning

-Predictive Analytics

-Information Retrieval

-Data Mining

-Signal and Video Processing

-Computer Visualization

-A selection of possible case scenarios will be made available at the beginning of the course.

Learning outcome

Knowledge: - Understanding of cutting-edge problems in computational and forensic sciences as well as their applications specific domains, as for example threat intelligence, automation of malware analysis, biometric identification, network intrusion detection, internet investigation, deep-package mining and multimedia-content analysis in forensics.

Skills: - The students can use relevant scientific methods in independent research and development in computational forensics. - The students are capable of carrying out an independent limited research or development project in computational forensics under supervision, following the applicable ethical rules.

General competence: - The students can work independently and are familiar with computational forensic terminology.

Learning methods and activities

  • Lectures
  • E-learning
  • PBL learning (Problem Baseed Learning)
  • Project work -Seminar(s)
  • Tutoring

Further on evaluation

Re-sit: The whole course must be repeated the next time the course is running.

Forms of assessment:

- The students have to deliver an essay and can deliver a project.

- In case a student decides to deliver both the essay and the project, then both will count for 50% towards the final grade, and both parts have to be passed to pass the course.

- In case the student only delivers an essay, then the final grade will be based 100% on the grade of the essay

Specific conditions

Admission to a programme of study is required:
Information Security (MIS)
Information Security (MISD)
Information Security (MISEB)

Required previous knowledge

Candidates must have passed IMT4133 Data Science for Security and Forensics.

Course materials

Scientific Articles related to the field of Specialization.

Credit reductions

Course code Reduction From To
IMT4641 5.0 AUTUMN 2017
More on the course



Version: 1
Credits:  7.5 SP
Study level: Second degree level


Term no.: 1
Teaching semester:  AUTUMN 2023

Language of instruction: English

Location: Gjøvik

Subject area(s)
  • Information Security
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Information Security and Communication Technology


Examination arrangement: Assignment (essay/project)

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Autumn ORD Assignment (essay/project) 100/100 ALLE





Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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