BIG DATA ANALYTICS AND MANAGEMENT (ENGLISH, NONTHESIS) | |||||
Master | TR-NQF-HE: Level 7 | QF-EHEA: Second Cycle | EQF-LLL: Level 7 |
Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
CMP5121 | Network Security and Cryptography | Fall | 3 | 0 | 3 | 8 |
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
Language of instruction: | English |
Type of course: | Departmental Elective |
Course Level: | |
Mode of Delivery: | Face to face |
Course Coordinator : | Assist. Prof. SELÇUK BAKTIR |
Course Lecturer(s): |
Assist. Prof. SELÇUK BAKTIR Assoc. Prof. YÜCEL BATU SALMAN |
Recommended Optional Program Components: | None |
Course Objectives: | This is an introductory course where fundamental concepts in cryptography and network security are explained. After completing the course, students will get basic understanding about encryption, decryption, stream ciphers, block ciphers, public-key cryptography, digital signatures, hash functions, message authentication codes and key distribution protocols. |
The students who have succeeded in this course; I. Gain knowledge on Symmetric key cryptography, block and stream ciphers, II. Gain knowledge on the AES algorithm, III. Gain knowledge on Public key cryptography and public key algorithms such as RSA, Diffie-Hellman, Elgamal and elliptic curve cryptography, IV. Gain knowledge on digital Signatures, V. Gain knowledge on hash functions, VI. Gain knowledge on key exchange protocols. |
Introduction and Review of Basics. Stream Ciphers. Advanced Encryption Standard (AES). Block Cipher Modes of Operation. Public-key Cryptography. The RSA Algorithm. Digital Signatures. Hash Functions. Message Authentication Codes. Discrete Logarithm Problem. Diffie-Hellman Key Exchange and ElGamal Encryption. Elliptic Curve Cryptography. Key Establishment Protocols. |
Week | Subject | Related Preparation |
1) | Introduction and review of basics. | |
2) | Stream Ciphers. | |
3) | Advanced Encryption Standard (AES). | |
4) | Block Cipher Modes of Operation. | |
5) | Public key cryptography. | |
6) | RSA algorithm. | |
7) | Midterm exam. | |
8) | Digital signatures. | |
9) | Hash functions. | |
10) | Message Authentication Codes. | |
11) | Discrete Logarithm Problem. | |
12) | Diffie-Hellman key exchange and ElGamal encryption. | |
13) | Elliptic curve cryptography. | |
14) | Key establishment protocols. |
Course Notes / Textbooks: | Understanding Cryptography, Christof Paar and Jan Pelzl, Springer 2010. |
References: |
Semester Requirements | Number of Activities | Level of Contribution |
Attendance | 14 | % 0 |
Homework Assignments | 4 | % 20 |
Presentation | 1 | % 10 |
Midterms | 1 | % 30 |
Final | 1 | % 40 |
Total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 60 | |
PERCENTAGE OF FINAL WORK | % 40 | |
Total | % 100 |
Activities | Number of Activities | Duration (Hours) | Workload |
Course Hours | 14 | 3 | 42 |
Study Hours Out of Class | 14 | 5 | 70 |
Presentations / Seminar | 2 | 3 | 6 |
Homework Assignments | 4 | 8 | 32 |
Midterms | 1 | 20 | 20 |
Final | 1 | 20 | 20 |
Total Workload | 190 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | To be able to follow and critically analyze scientific literature and use it effectively in solving engineering problems. | 2 |
2) | To be able to design, plan, implement and manage original projects related to Big Data Analytics and Management. | 1 |
3) | To be able to carry out studies on Big Data Analytics and Management independently, take scientific responsibility and critically evaluate the results obtained. | 1 |
4) | Effectively present the results of his/her research and projects in written, oral and visual form in accordance with academic standards. | 1 |
5) | To be able to conduct independent research in the field of Big Data Analytics and Management, develop original ideas and transfer this knowledge to practice. | 1 |
6) | Uses advanced theoretical and practical knowledge specific to the field of Big Data Analytics and Management effectively. | 1 |
7) | Acts in accordance with professional, scientific and ethical values; takes responsibility by considering the social, environmental and ethical impacts of engineering applications. | 1 |