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Cyber Threat Information and Data-analytics (5 cr)

Code: TTC6030-3012

General information


Enrollment
18.11.2024 - 09.01.2025
Registration for the implementation has ended.
Timing
13.01.2025 - 30.04.2025
Implementation is running.
Number of ECTS credits allocated
5 cr
Local portion
0 cr
Virtual portion
5 cr
Mode of delivery
Online learning
Unit
School of Technology
Teaching languages
English
Seats
0 - 35
Degree programmes
Bachelor's Degree Programme in Information and Communications Technology
Teachers
Tarja Ajo
It Instituutti
Heikki Järvinen
Groups
TTV22S5
Tieto- ja viestintätekniikka (AMK)
TTV22S2
Tieto- ja viestintätekniikka (AMK)
TTV22S3
Tieto- ja viestintätekniikka (AMK)
TIC22S1
Bachelor's Degree Programme in Information and Communications Technology
TTV22S1
Tieto- ja viestintätekniikka (AMK)
TTV22S4
Tieto- ja viestintätekniikka (AMK)
ZJA25KTIKY2
Avoin amk, Kyberturvallisuus 2, Verkko
Course
TTC6030

Realization has 14 reservations. Total duration of reservations is 35 h 0 min.

Time Topic Location
Mon 13.01.2025 time 11:15 - 13:45
(2 h 30 min)
Cyber Threat Information and Data-analytics TTC6030-3012
Online
Mon 20.01.2025 time 11:15 - 13:45
(2 h 30 min)
Cyber Threat Information and Data-analytics TTC6030-3012
Online
Mon 27.01.2025 time 11:15 - 13:45
(2 h 30 min)
Cyber Threat Information and Data-analytics TTC6030-3012
Online
Mon 03.02.2025 time 11:15 - 13:45
(2 h 30 min)
Cyber Threat Information and Data-analytics TTC6030-3012
Online
Mon 10.02.2025 time 11:15 - 13:45
(2 h 30 min)
Cyber Threat Information and Data-analytics TTC6030-3012
Online
Mon 17.02.2025 time 11:15 - 13:45
(2 h 30 min)
Cyber Threat Information and Data-analytics TTC6030-3012
Online
Mon 03.03.2025 time 11:15 - 13:45
(2 h 30 min)
Cyber Threat Information and Data-analytics TTC6030-3012
Online
Mon 10.03.2025 time 11:15 - 13:45
(2 h 30 min)
Cyber Threat Information and Data-analytics TTC6030-3012
Online
Mon 17.03.2025 time 11:15 - 13:45
(2 h 30 min)
Cyber Threat Information and Data-analytics TTC6030-3012
Online
Mon 24.03.2025 time 11:15 - 13:45
(2 h 30 min)
Cyber Threat Information and Data-analytics TTC6030-3012
Online
Mon 31.03.2025 time 11:15 - 13:45
(2 h 30 min)
Cyber Threat Information and Data-analytics TTC6030-3012
Online
Mon 07.04.2025 time 11:15 - 13:45
(2 h 30 min)
Cyber Threat Information and Data-analytics TTC6030-3012
Online
Mon 14.04.2025 time 11:15 - 13:45
(2 h 30 min)
Cyber Threat Information and Data-analytics TTC6030-3012
Online
Mon 28.04.2025 time 11:15 - 13:45
(2 h 30 min)
Cyber Threat Information and Data-analytics TTC6030-3012
Online
Changes to reservations may be possible.

Evaluation scale

0-5

Objective

Purpose:
You understand the principles of threat intelligence, its types and exploitability in cyber defense. You learn to utilise data analytics methods in handling great amounts of data from cyber security perspective. You understand the significance of enriching the data with external data sources.

EUR-ACE Competences:
Multidisciplinary competences 
Knowledge and understanding 
Engineering practice 
Communication and team-working 

Learning outcomes:
You know the basic concepts of threat intelligence, you understand the purpose of threat intelligence and data-analytics, you can apply correct methods to the specific problems, and you can do data-analytics using Python programming language.

Content

Content:
Principles and forms of threat intelligence
Exploitability of threat intelligence
Methods of data analytics in handling data and exploitation
Enriching threat intelligence with external sources

Materials

Materials in the e-learning environment.

Teaching methods

- lectures
- independent study
- distance learning
- webinars
- small group learning
- exercises
- learning tasks

Employer connections

- visiting lecturers

Exam schedules

The possible date and method of the exam will be announced in the course opening.

Completion alternatives

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit (1 Cr) corresponds to an average of 27 hours of work.

- lectures 52 h
- exercises 15 h
- assignment 36 h
- independent study 32 h
Total 135 h

Assessment criteria, satisfactory (1)

Sufficient 1: You know superficially the principles and types of threat intelligence in cyber defense. You are able to select the most common methods for the problem to be solved and are able to apply the most common methods. Additionally, you are able to give a constricted assessment of their implementation and justify the conclusions.

Satisfactory 2: You knows the principles and types of threat intelligence in cyber defense. You are able to select the most common methods for the problem to be solved and you are to apply their technical competence to practice. Additionally, You are able to assess their implementation superficially and justify the conclusions.

Assessment criteria, good (3)

Good 3: You know the principles, types and exploitability of threat intelligence in cyber defense. You are able to select the most common methods for the problem to be solved and are able to apply their technical competence to practice. Additionally, you are able to assess their implementation versatilely and justify the conclusions.

Very good 4: You know the principles, types and exploitability of threat intelligence in cyber defense. You are able to select the correct methods for the problem to be solved and are able to apply their technical competence to practice. Additionally, you are able to assess their implementation versatilely and justify the conclusions.

Assessment criteria, excellent (5)

Excellent 5: You know the principles, types and exploitability of threat intelligence in cyber defense. You are able to select the correct methods for the problem to be solved and are able to apply their technical competence to practice. Additionally, you are able to assess their implementation critically and justify the conclusions.

Further information

The course assessment methods will be presented during the first meeting. Prior knowledge of Python programming language is recommended.

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