Further EDUCATIONAL ACTIVITIES
Academic Year 2023/2024 - Teacher: FRANCESCO GUARNERAExpected Learning Outcomes
The course is aimed at providing the student with skills relating to the application of scientific methodologies in forensic investigations. Students will develop the skills necessary to understand the processes required to obtain reliable information using experimental data. Emphasis is placed on concepts and principles that explain the uses and pitfalls of scientific data and on developing the knowledge and skills necessary for processing computer data for forensic investigations.
Course Structure
Lectures and case studies.
Required Prerequisites
Knowledge of basic computer science concepts.
Attendance of Lessons
Mandatory
Detailed Course Content
The course is structured as follows:
1. The IT crime scene
2. Introduction to Digital Forensics
3. Multimedia Forensics for image manipulation
4. ENFSI Best Practice Manual: approach to digital crime
5. Photo Response Non Uniformity (PRNU)
6. Deepfake
7. Adversarial Learning and anti-forensic techniques
Textbook Information
Evgeny Katz, Jan Halámek, Forensic Science: A Multidisciplinary Approach, Wiley, 2016
John Sammons The Basics of Digital Forensics: The Primer for Getting Started in Digital Forensics - Syngress; 1 edition (2012)
Course Planning
| Subjects | Text References | |
|---|---|---|
| 1 | IT Crime Scene | |
| 2 | Introduction to Digital Forensics | |
| 3 | Multimedia Forensics for image manipulation | |
| 4 | ENFSI Best Practice Manual | |
| 5 | Photo Response Non Uniformity (PRNU) | |
| 6 | Deepfake | |
| 7 | Adversarial Learning and anti-forensic techniques |
Learning Assessment
Learning Assessment Procedures
Project and/or presentation on a topic covered in class
Examples of frequently asked questions and / or exercises
Analysis, collection and conservation of finds
Best Practices for Image Manipulation Verification
Description of DeepFake