Description
PRESENTATION
The course will cover aspects relating to the identification, retrieval of evidence sources in a correct manner, so that they can also be evaluated in civil or criminal proceedings, analysis and presentation of conclusions. Practical laboratory part, based on Open Source and freeware software. The course includes an overview of AI, machine learning, deep learning, genetic algorithms, applications in cybersecurity and digital forensics and the ethical issue of BIAS (bias) in datasets.
PURPOSE
The aim of the course is to provide a solid foundation for engaging in activities in the world of digital investigation, a subject that is constantly changing and evolving. During the course, participants will also learn how to find hidden files, recover deleted data and duplicate intact and non-repudiable information, including through the use of classroom tools and the analysis of real case studies. In addition, there will be an introduction to Artificial Intelligence and how it can be integrated into cybersecurity and digital forensics.
REQUIREMENTS
Knowledge of the Windows operating system, basics of Linux and networking. No specific requirements for the Legal part.
RECIPIENTS
Engineers, computer scientists, mathematicians, physicists.
COMPETENCES
Medium/high knowledge of computer science and mathematics.
WHAT TO BRING
A laptop running Windows with the following tools installed: FTK Imager, Arsenal, Autopsy, VirtualBox/VMware. You will also need TWO 128 GB USB pendrive.
WHAT YOU WILL RECEIVE AS MATERIAL
Teaching material, PDF slides and Certificate of Participation
NOTES
Lunches & Coffee breaks included
Admission ticket to HackInBo® Classic Edition on 7 June 2025 included!