YBS450


Course Title Course Code Program Level
SOCIAL NETWORK ANALYSIS YBS450 International Trade and Finance B.A. / B.Sc.

Course Term
(Course Semester)
Teaching and Learning Methods
Credits
Theory Practice Lab Projects/Field Work Seminars/Workshops Other Total Credits ECTS Credits
08
(Spring)
42 30 53 128 3 5

Teaching Staff
Language of Instruction Türkçe (Turkish)
Type Of Course Elective
Prerequisites
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) 1. Anticipate vulnerability areas and prevent social engineering attempts. 2. Acquire the knowledge, skills, and foresight to conduct awareness-raising activities for personnel in their workplace. 3. Model the data of a social network using graph data structures. 4. Identify and interpret characteristic structures in networks. 5. Calculate centrality metrics of the network and interpret the results. 6. 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 (%)
Practice (%)
Labs (%)
Projects/Field Work (%)
Seminars/Workshops (%)
Final (%) 60
Other (%)
Total(%) 100
Course Book (s) and/or References 1. “Kullanıcı Güvenliği Eğitimi”, TÜBİTAK BİLGEM Siber Güvenlik Enstitüsü 2. “Sosyal Mühendisin Maskesini Düşürmek”, Christopher Hadnagy. 3. “Sosyal Mühendislik Saldırıları”, Okan Yıldız, Alper Başaran. 4. “Sosyal Ağ Analizi”, Prof.Dr. Necmi GÜRSAKAL. 5. Lecture presentations and notes.
Work Placement(s)
The Relationship between Program Qualifications (PQ) and Course Learning Outcomes (LO)