Cyber Threat Information and Data-analytics (5 cr)
Code: TTC6030-3012
General information
- Enrollment
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18.11.2024 - 09.01.2025
Registration for the implementation has ended.
- Timing
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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
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TTV22S5Tieto- ja viestintätekniikka (AMK)
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TTV22S2Tieto- ja viestintätekniikka (AMK)
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TTV22S3Tieto- ja viestintätekniikka (AMK)
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TIC22S1Bachelor's Degree Programme in Information and Communications Technology
-
TTV22S1Tieto- ja viestintätekniikka (AMK)
-
TTV22S4Tieto- ja viestintätekniikka (AMK)
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ZJA25KTIKY2Avoin amk, Kyberturvallisuus 2, Verkko
- Course
- TTC6030
Realization has 14 reservations. Total duration of reservations is 35 h 0 min.
Time | Topic | Location |
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Mon 13.01.2025 time 11:15 - 13:45 (2 h 30 min) |
Cyber Threat Information and Data-analytics TTC6030-3012 |
Online
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Mon 20.01.2025 time 11:15 - 13:45 (2 h 30 min) |
Cyber Threat Information and Data-analytics TTC6030-3012 |
Online
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Mon 27.01.2025 time 11:15 - 13:45 (2 h 30 min) |
Cyber Threat Information and Data-analytics TTC6030-3012 |
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Mon 03.02.2025 time 11:15 - 13:45 (2 h 30 min) |
Cyber Threat Information and Data-analytics TTC6030-3012 |
Online
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Mon 10.02.2025 time 11:15 - 13:45 (2 h 30 min) |
Cyber Threat Information and Data-analytics TTC6030-3012 |
Online
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Mon 17.02.2025 time 11:15 - 13:45 (2 h 30 min) |
Cyber Threat Information and Data-analytics TTC6030-3012 |
Online
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Mon 03.03.2025 time 11:15 - 13:45 (2 h 30 min) |
Cyber Threat Information and Data-analytics TTC6030-3012 |
Online
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Mon 10.03.2025 time 11:15 - 13:45 (2 h 30 min) |
Cyber Threat Information and Data-analytics TTC6030-3012 |
Online
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Mon 17.03.2025 time 11:15 - 13:45 (2 h 30 min) |
Cyber Threat Information and Data-analytics TTC6030-3012 |
Online
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Mon 24.03.2025 time 11:15 - 13:45 (2 h 30 min) |
Cyber Threat Information and Data-analytics TTC6030-3012 |
Online
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Mon 31.03.2025 time 11:15 - 13:45 (2 h 30 min) |
Cyber Threat Information and Data-analytics TTC6030-3012 |
Online
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Mon 07.04.2025 time 11:15 - 13:45 (2 h 30 min) |
Cyber Threat Information and Data-analytics TTC6030-3012 |
Online
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Mon 14.04.2025 time 11:15 - 13:45 (2 h 30 min) |
Cyber Threat Information and Data-analytics TTC6030-3012 |
Online
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Mon 28.04.2025 time 11:15 - 13:45 (2 h 30 min) |
Cyber Threat Information and Data-analytics TTC6030-3012 |
Online
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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.