312-49V11 · Question #127
As an IoT forensic investigator, you are tasked with investigating a cybercrime involving a compromised Smart TV and other IoT devices. The investigation requires extracting data from various IoT…
The correct answer is B. MD-NEXT. This question maps directly to CHFI v11 objectives under Mobile and IoT Forensics and Tools for IoT Device Forensics. IoT investigations often involve heterogeneous devices with different operating systems, storage mechanisms, and acquisition challenges. CHFI v11 emphasizes the…
Question
As an IoT forensic investigator, you are tasked with investigating a cybercrime involving a compromised Smart TV and other IoT devices. The investigation requires extracting data from various IoT devices, including drones, wearables, and SD cards, to gather crucial evidence. You need a tool capable of performing both physical and logical extractions from these devices, covering mobile devices running Android, iOS, Tizen OS, and chip-off memory sources. Which of the following tools would be most suitable for this investigation?
Options
- ADoubleSpace
- BMD-NEXT
- CEpochConverter
- DSystemctl
How the community answered
(27 responses)- A4% (1)
- B78% (21)
- C7% (2)
- D11% (3)
Explanation
This question maps directly to CHFI v11 objectives under Mobile and IoT Forensics and Tools for IoT Device Forensics. IoT investigations often involve heterogeneous devices with different operating systems, storage mechanisms, and acquisition challenges. CHFI v11 emphasizes the need for specialized forensic tools that support both logical and physical extraction, including advanced techniques such as chip-off and SD card analysis, to ensure comprehensive evidence MD-NEXT is a purpose-built digital forensic tool designed for mobile and IoT investigations. It supports forensic acquisition and analysis across a wide range of platforms, including Android, iOS, Tizen OS, wearables, drones, smart TVs, and removable media. Importantly, MD-NEXT provides capabilities for logical extraction, physical imaging, file system parsing, and chip-off memory analysis, which are critical when dealing with damaged, locked, or non-standard IoT
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