Digital forensics

efficiency of data recovery software in scenarios of physical and logical damage

Abstract

This article discusses the importance of digital forensic analysis in recovering data from partially damaged media, focusing on the restoration of information that has been accidentally or intentionally deleted. Data recovery has become an essential skill for digital forensic experts, particularly in criminal and corporate investiga-tions, where preserving evidence is crucial. With the rise of cybercrimes, the ability to restore inaccessible data due to physical or logical damage is fundamental to ensuring the delivery of secure evidence. The research evaluates the effectiveness of different traditional data recovery software, such as Cellebrite and IPED, and emerging AI-based tools, such as Deep Recovery AI, comparing their ability to re-store information under varying damage conditions. The methodology involves comparing the recovery rate, data integrity, and processing time of the analyzed software. The expected results aim to contribute to digital forensic practices by highlighting the importance of reliable and efficient tools for data restoration, which are essential for resolving investigative cases.