| Teaching Staff
|
Dr.Öğr. Üyesi Fatih SAĞLAM |
| Language of Instruction |
Türkçe (Turkish) |
| Type Of Course |
Elective |
| Prerequisites |
None |
| Recommended Optional Programme Component |
|
| Course Objectives |
The aim of this course is to anticipate cyber threats and attacks that may arise from the world of social engineering and to develop countermeasures. It seeks to equip students with the knowledge and skills necessary to assess the security and vulnerabilities of networks using social network analysis techniques and methods, allowing for the implementation of security-enhancing measures. |
| Course Content |
In this course, the discipline of social engineering, which is based on vulnerabilities, and its methods will be discussed. It will cover the measures developed against social engineering and awareness, examining a network structure from the perspective of social networks and calculating analysis metrics, supported by the Gephi software for practical applications. |
| Learning Outcomes (LO) |
Anticipate vulnerability areas and prevent social engineering attempts.
Acquire the knowledge, skills, and foresight to conduct awareness-raising activities for personnel in their workplace.
Model the data of a social network using graph data structures.
Identify and interpret characteristic structures in networks.
Calculate centrality metrics of the network and interpret the results.
Use Gephi software to visualize networks, conduct analyses, and interpret the results. |
| Mode of Delivery |
Face to face |
| Course Outline |
| Week |
Topics |
| 1. Week |
Course Introduction, Objectives, Goals, and Process |
| 2. Week |
Social Engineering – INTRODUCTION |
| 3. Week |
Methods of Social Engineering |
| 4. Week |
Information Gathering in Social Engineering |
| 5. Week |
Social Networks – INTRODUCTION |
| 6. Week |
Graph Data Structures and Representation Methods |
| 7. Week |
Characteristic Structures in Graphs - 1 |
| 8. Week |
MIDTERM EXAM |
| 9. Week |
Characteristic Structures in Graphs - 2 |
| 10. Week |
Network Analysis – Metrics for the Entire Network |
| 11. Week |
Network Analysis – Node-Specific Metrics |
| 12. Week |
Creating, Drawing, and Analyzing Networks with Gephi |
| 13. Week |
Creating, Drawing, and Analyzing Networks with Gephi |
| 14. Week |
Creating, Drawing, and Analyzing Networks with Gephi |
|
| Assessment |
| |
Percentage(%) |
| Mid-term (%) |
40 |
| Quizes (%) |
|
| Homeworks/Term papers (%) |
Final sınavına %20 oranında etki edecektir. |
| Practice (%) |
|
| Labs (%) |
|
| Projects/Field Work (%) |
|
| Seminars/Workshops (%) |
|
| Final (%) |
60 |
| Other (%) |
|
| Total(%) |
100 |
|
| Course Book (s) and/or References |
|
| Work Placement(s) |
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| The Relationship between Program Qualifications (PQ) and Course Learning Outcomes (LO) |
| PQ1 | PQ2 | PQ3 | PQ4 | PQ5 | PQ6 | PQ7 | PQ8 | PQ9 | PQ10 | LO1 | | 2 | 5 | | 3 | | 5 | 1 | 5 | 5 | LO2 | | 5 | 5 | | 3 | | 3 | 3 | 5 | 5 | LO3 | 5 | | 5 | 4 | 2 | | 5 | | 2 | | LO4 | | 5 | 5 | 5 | 5 | 4 | | | 1 | | ÖLO5 | 4 | | 4 | 3 | 5 | | 4 | 2 | | | LO6 | 5 | | 5 | 5 | 5 | 4 | 5 | 5 | | 1 |
|