IoTフォレンジック調査員として、あなたはスマートテレビやその他のIoTデバイスが侵害されたサイバー犯罪の捜査を任されています。この捜査では、ドローン、ウェアラブル、SDカードなど、様々なIoTデバイスからデータを抽出し、重要な証拠を収集する必要があります。Android、iOS、Tizen OSを搭載したモバイルデバイス、そしてチップオフメモリソースなど、これらのデバイスから物理的および論理的なデータ抽出を実行できるツールが必要です。この捜査に最適なツールは次のうちどれでしょうか?
正解:B
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 collection.
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 devices.
The other options are not suitable for this scenario. DoubleSpace is a disk compression utility, EpochConverter is used for timestamp conversion, and Systemctl is a Linux service management command.
None provide forensic acquisition capabilities. Therefore, MD-NEXT is the most suitable and CHFI v11- aligned tool for comprehensive IoT and mobile device forensic investigations.