Weaponized IoT: A Comprehensive Comparative Forensic Analysis of Hacker Raspberry Pi and PC Kali Linux Machine
The proliferation of Internet of Things (IoT) devices presents significant challenges for cybersecurity and digital forensics, particularly as these devices have become increasingly weaponised for malicious activities. This research focuses on the forensic analysis capabilities of Raspberry Pi devic...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
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| Series: | IoT |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2624-831X/6/1/18 |
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| Summary: | The proliferation of Internet of Things (IoT) devices presents significant challenges for cybersecurity and digital forensics, particularly as these devices have become increasingly weaponised for malicious activities. This research focuses on the forensic analysis capabilities of Raspberry Pi devices configured with Kali Linux, comparing their forensic capabilities to conventional PC-based forensic investigations. The study identifies key gaps in existing IoT forensic methodologies, including limited tool compatibility, constrained data retention, and difficulties in live memory analysis due to architectural differences. The research employs a testbed-based approach to simulate cyberattacks on both platforms, capturing and analysing forensic artefacts such as system logs, memory dumps, and network traffic. The research findings reveal that while traditional PCs offer extensive forensic capabilities due to superior storage, tool support, and system logging, Raspberry Pi devices present significant forensic challenges, primarily due to their ARM architecture and limited forensic readiness. The study emphasises the need for specialised forensic tools tailored to IoT environments and suggests best practices to enhance forensic investigation capabilities in weaponised IoT scenarios. This research contributes to the field by bridging the gap between theoretical frameworks and real-world forensic investigations, offering insights into the evolving landscape of IoT forensics and its implications for digital evidence collection, analysis, and forensic readiness. |
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| ISSN: | 2624-831X |