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SECTION I: GENERAL INFORMATION ABOUT THE COURSE

Course Code Course Name Year Semester Theoretical Practical Credit ECTS
70610MEEOS-CME0590 Cryptology 0 Spring 3 0 3 6
Course Type :
Cycle: Master      TQF-HE:7. Master`s Degree      QF-EHEA:Second Cycle      EQF-LLL:7. Master`s Degree
Language of Instruction: English
Prerequisities and Co-requisities: N/A
Mode of Delivery: Face to face
Name of Coordinator: Dr. Öğr. Üyesi DUYGU DEMİRAY AKKAYA
Dersin Öğretim Eleman(lar)ı:
Dersin Kategorisi:

SECTION II: INTRODUCTION TO THE COURSE

Course Objectives & Content

Course Objectives: This course aims to introduce cryptographic algorithms and methods in an applied manner.
Course Content: It covers explaining encryption and decryption process and necessary mathematical algorithms so that students can embrace significance of cryptology in relation to the information security. Topics include: classical encryption techniques, symmetric and asymmetric encryption, hash algorithms and examining usage areas of cryptographic applications.

Course Learning Outcomes (CLOs)

Course Learning Outcomes (CLOs) are those describing the knowledge, skills and competencies that students are expected to achieve upon successful completion of the course. In this context, Course Learning Outcomes defined for this course unit are as follows:
Knowledge (Described as Theoritical and/or Factual Knowledge.)
  1) Learns the basics of cryptology.
  2) Understands the role of cryptology plays in information systems security.
  3) Has knowledge about working principles of conventional and modern encryption algorithms.
Skills (Describe as Cognitive and/or Practical Skills.)
  1) Identifies and classifies the encryption algorithms.
  2) Can implement encryption algorithms.
  3) Can implement cryptanalysis algorithms.
Competences (Described as "Ability of the learner to apply knowledge and skills autonomously with responsibility", "Learning to learn"," Communication and social" and "Field specific" competences.)
  1) Implements the techniques and algorithms (learned in the course) in an individual project.

Weekly Course Schedule

Week Subject
Materials Sharing *
Related Preparation Further Study
1) Fundamental Concepts of Cryptology
2) Introduction to Cryptology and Steganography
3) Encryption Techniques (Symmetric)
4) Encryption Techniques (Symmetric)
5) Block Ciphers
6) One time pad and Stream Ciphers
7) Hash Functions
8) Midterm Exam
9) Asymmetric Encryption
10) Asymmetric Encryption
11) Digital Signatures
12) Crypto and Physical World
13) Literature Review Report Delivery & Presentations
14) Semester review
*These fields provides students with course materials for their pre- and further study before and after the course delivered.

Recommended or Required Reading & Other Learning Resources/Tools

Course Notes / Textbooks: Cryptography and Network Security, W. Stallings, 5th ed., John Wiley & Sons, Inc, 2010.

Cryptography: Theory and Practice, D.G. Stinson and M.B. Paterson, 4th edition, CRC Press, 2019.

An Introduction to Cryptography, R.A. Mollin, 2nd edition, Chapman and Hall, 2006.

Introduction Cryptography with Coding Theory, W. Trappe, L. C. Washington, Prentice Hall, 2002.

Hacking Secret Ciphers with Python, A. Sweigart, 2013.
References: Cryptography: An Introduction, N. Smart, 3rd edition,
available: https://www.cs.umd.edu/~waa/414-F11/IntroToCrypto.pdf

DERS ÖĞRENME ÇIKTILARI - PROGRAM ÖĞRENME ÇIKTILARI İLİŞKİSİ

Contribution of The Course Unit To The Programme Learning Outcomes

Ders Öğrenme Çıktıları (DÖÇ)

1

2

3

4

5

6

7

Program Öğrenme Çıktıları (PÖÇ)
1) Owns advanced theoretical and applied knowledge in the field of computer science and engineering.
2) Owns the comprehensive knowledge about advanced techniques and methods and their limitations applied in the field of computer science and engineering.
3) Reaches knowledge broadly and deeply by application and development in the field of computer science and engineering, evaluates, interprets and applies knowledge.
4) Complements and applies knowledge with scientific methods using uncertain, limited or incomplete data; can use information from different disciplines together.
5) Defines the problem, accesses data, uses knowledge from different disciplines, designs researches, designs system and process, develops solution methods in order to solve current problems in the field of computer science and engineering.
6) Can work effectively in disciplinary and multi-disciplinary teams, lead such teams and develop solution approaches in complex situations; can work independently and take responsibility.
7) Has awareness of the new and developing applications of his/her profession, examines and learns them when needed.
8) Has the necessary skills and competencies to perform his/her profession in the most effective way and to constantly improve himself/herself.
9) Acquires communication in a Foreign Language (English) competence defined on the level of at least B2 in European Language Portfolio.
10) Observes social, scientific and ethical values in the stages of data collection, interpretation, announcement and in all professional activities.
11) Knows the social, environmental, health, safety, legal aspects of engineering applications, project management and business life applications, and is aware of the constraints they impose on engineering applications.

SECTION III: RELATIONSHIP BETWEEN COURSE UNIT AND COURSE LEARNING OUTCOMES (CLOs)

Level of Contribution of the Course to PLOs

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Programme Learning Outcomes Contribution Level (from 1 to 5)
1) Owns advanced theoretical and applied knowledge in the field of computer science and engineering.
2) Owns the comprehensive knowledge about advanced techniques and methods and their limitations applied in the field of computer science and engineering.
3) Reaches knowledge broadly and deeply by application and development in the field of computer science and engineering, evaluates, interprets and applies knowledge.
4) Complements and applies knowledge with scientific methods using uncertain, limited or incomplete data; can use information from different disciplines together.
5) Defines the problem, accesses data, uses knowledge from different disciplines, designs researches, designs system and process, develops solution methods in order to solve current problems in the field of computer science and engineering.
6) Can work effectively in disciplinary and multi-disciplinary teams, lead such teams and develop solution approaches in complex situations; can work independently and take responsibility.
7) Has awareness of the new and developing applications of his/her profession, examines and learns them when needed.
8) Has the necessary skills and competencies to perform his/her profession in the most effective way and to constantly improve himself/herself.
9) Acquires communication in a Foreign Language (English) competence defined on the level of at least B2 in European Language Portfolio.
10) Observes social, scientific and ethical values in the stages of data collection, interpretation, announcement and in all professional activities.
11) Knows the social, environmental, health, safety, legal aspects of engineering applications, project management and business life applications, and is aware of the constraints they impose on engineering applications.

SECTION IV: TEACHING-LEARNING & ASSESMENT-EVALUATION METHODS OF THE COURSE

Teaching & Learning Methods of the Course

(All teaching and learning methods used at the university are managed systematically. Upon proposals of the programme units, they are assessed by the relevant academic boards and, if found appropriate, they are included among the university list. Programmes, then, choose the appropriate methods in line with their programme design from this list. Likewise, appropriate methods to be used for the course units can be chosen among those defined for the programme.)
Teaching and Learning Methods defined at the Programme Level
Teaching and Learning Methods Defined for the Course
Lectures
Discussion
Problem Solving
Views
Project Preparation

Assessment & Evaluation Methods of the Course

(All assessment and evaluation methods used at the university are managed systematically. Upon proposals of the programme units, they are assessed by the relevant academic boards and, if found appropriate, they are included among the university list. Programmes, then, choose the appropriate methods in line with their programme design from this list. Likewise, appropriate methods to be used for the course units can be chosen among those defined for the programme.)
Aassessment and evaluation Methods defined at the Programme Level
Assessment and Evaluation Methods defined for the Course
Midterm
Presentation
Final Exam
Quiz

Contribution of Assesment & Evalution Activities to Final Grade of the Course

Measurement and Evaluation Methods # of practice per semester Level of Contribution
Quizzes 2 % 10.00
Project 2 % 20.00
Midterms 1 % 20.00
Semester Final Exam 1 % 50.00
Total % 100
PERCENTAGE OF SEMESTER WORK % 50
PERCENTAGE OF FINAL WORK % 50
Total % 100

SECTION V: WORKLOAD & ECTS CREDITS ALLOCATED FOR THE COURSE

WORKLOAD OF TEACHING & LEARNING ACTIVITIES
Teaching & Learning Activities # of Activities per semester Duration (hour) Total Workload
Course 14 3 42
Laboratory 0 0 0
Application 0 0 0
Special Course Internship (Work Placement) 0 0 0
Field Work 0 0 0
Study Hours Out of Class 14 3 42
Presentations / Seminar 0 0 0
Project 2 5 10
Homework Assignments 0 0 0
Total Workload of Teaching & Learning Activities - - 94
WORKLOAD OF ASSESMENT & EVALUATION ACTIVITIES
Assesment & Evaluation Activities # of Activities per semester Duration (hour) Total Workload
Quizzes 2 5 10
Midterms 1 20 20
Semester Final Exam 1 30 30
Total Workload of Assesment & Evaluation Activities - - 60
TOTAL WORKLOAD (Teaching & Learning + Assesment & Evaluation Activities) 154
ECTS CREDITS OF THE COURSE (Total Workload/25.5 h) 6