Prospectus

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Data Mining for Cyber Security

Course
2017-2018

Admission requirements

Admission only after intake, see website of the Cyber Security Academy
Elective in master’s programme Cyber Security

Description

The course will provide an extensive overview of data mining and data stream mining techniques and their applications to cyber security. Some applications of these techniques to real-time detection of deviations in data streams, detection of misuse of information systems, fraud detection, detection of DoS attacks, etc. will be discussed in depth. Additionally, practical work with real data will provide the participants some hands-on experience with applying data mining to real-life problems.

Course objectives

Participants have:

  • technical understanding of ICT systems, technical measures and interventions in relation to cyber security questions

  • knowledge and understanding of the potential and limitations of data monitoring & data analytics tools to detect cyber security incidents in cyberspace to apply data mining tools on real-world examples

Timetable

5 Fridays from 9.30 until 17.00, either in April/May or in June/July, to be scheduled dependant on preferences of participants

Mode of instruction

Lectures, seminars, exercises, class discussion
Lecturers: Dr. Wojtek Kowalczyk

Course Load

4 EC

Assessment method

Assignment (50%), presentation (10%), written exam (40%)
No compensation is possible for assignments of 30% or more.

Blackboard

Yes, for posting slides of lectures, relevant literature and assignments

Reading list

Compulsory literature and literature for further consultation will be announced via Blackboard

Registration

No registration is required for lectures and exams.

Contact

Dr. Wojtek Kowalczyk Drs. Mireille Snels, programme manager Pauline Hutten MSc, programme coordinator

Remarks

For more information see the website of the Cyber Security Academy