CYS5172 Advanced Computer ForensicsBahçeşehir UniversityDegree Programs COMPUTER ENGINEERING (ENGLISH, THESIS)General Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
COMPUTER ENGINEERING (ENGLISH, THESIS)
Master TR-NQF-HE: Level 7 QF-EHEA: Second Cycle EQF-LLL: Level 7

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
CYS5172 Advanced Computer Forensics Fall 3 0 3 12
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction: English
Type of course: Departmental Elective
Course Level:
Mode of Delivery: Face to face
Course Coordinator : Dr. Öğr. Üyesi AHMET NACİ ÜNAL
Recommended Optional Program Components: None
Course Objectives: To teach advanced level computer forensic techniques.

Learning Outcomes

The students who have succeeded in this course;
Effective use of artificial intelligence in the areas of forensics, in this context, ensure research in the field of artificial intelligence.

Course Content

Natural and Artificial Intelligence. Intuitive Problem Resolution. Information Modeling and Predicate Logic. Logic Programming. Applicability of Expert Systems and Forensic Computing. Applicability of Artificial Neural Networks and Forensic Computing. Applicability of Genetic Algorithms and Forensic Computing. Applicability of Fuzzy Logic and Forensic Computing. Applicability of Natural Language Processing and Forensic Computing. Applicability of Audio Processing and Forensic Computing. Applicability of Image Processing and Forensic Computing. Biometry Artificial Intelligence Applications I (Face Detection). Biometry Artificial Intelligence Applications II Fingerprint). Biometry Artificial Intelligence Applications III Character Recognition, Handwriting).

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Natural and Artificial Intelligence Lecturer notes
2) Intuitive Problem Resolution Lecturer notes
3) Information Modeling and Predicate Logic Lecturer notes
4) Logic Programming Lecturer notes
5) Applicability of Expert Systems and Forensic Computing Lecturer notes
6) Applicability of Artificial Neural Networks and Forensic Computing Lecturer notes
7) Applicability of Genetic Algorithms and Forensic Computing Lecturer notes
8) Applicability of Fuzzy Logic and Forensic Computing Lecturer notes
9) Applicability of Natural Language Processing and Forensic Computing Lecturer notes
10) Applicability of Audio Processing and Forensic Computing Lecturer notes
11) Applicability of Image Processing and Forensic Computing Lecturer notes
12) Biometry Artificial Intelligence Applications I (Face Detection) Lecturer notes
13) Biometry Artificial Intelligence Applications II Fingerprint) Lecturer notes
14) Biometry Artificial Intelligence Applications III Character Recognition, Handwriting) Lecturer notes

Sources

Course Notes / Textbooks: Network Forensics, Ric Messier. 2017.
Mobile Forensic Investigations: A Guide to Evidence Collection, Analysis, and Presentation. Lee Reiber, 2016.
References: Ders notları

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Attendance 10 % 0
Homework Assignments 4 % 10
Presentation 1 % 10
Midterms 1 % 20
Final 1 % 60
Total % 100
PERCENTAGE OF SEMESTER WORK % 40
PERCENTAGE OF FINAL WORK % 60
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 3 42
Study Hours Out of Class 14 12 168
Presentations / Seminar 2 3 6
Homework Assignments 4 8 32
Midterms 1 20 20
Final 1 20 20
Total Workload 288

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution