IoT Challenges in Digital Forensics

The proliferation of Internet of Things (IoT) devices has transformed the way we interact with the digital world, embedding connectivity into everyday objects. However, this advancement has brought forth significant challenges for digital forensics investigators.

As it has been rightly mentioned by various researchers, the evidence in IoT devices is different from traditional digital devices. For example, Containing an IoT breach is increasingly challenging. Evidence is no longer restricted to a PC or mobile device, but can be found in vehicles, RFID cards, and smart devices.

Citation: A. MacDermott, T. Baker and Q. Shi, "Iot Forensics: Challenges for the Ioa Era," 2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS), Paris, France, 2018, pp. 1-5, doi: 10.1109/NTMS.2018.8328748.

To address these challenges, it is important for digital forensics to have robust tools and methodologies that are capable of handling the complexity and heterogeneity of IoT systems. While there are many things to be looked into, I'd like to talk of following 3 things I think will have great impact on this challenge:

1. Utilize Machine Learning - Implement machine learning algorithms to analyze patterns within large-scale IoT data, automating the identification of suspicious activities and reducing manual analysis efforts
2. Develop Universal Extraction Tools - Invest in the development of versatile tools capable of extracting data from multiple IoT devices, reducing the time spent on developing device-specific solutions
3. Advocate for Public-Private Collaboration - Facilitate partnerships between law enforcement agencies, private sector companies, and academia to share knowledge, expertise, and resources, fostering a holistic approach to IoT forensic challengesLastly, we must remember that these solutions require a multidisciplinary approach, involving not just technology but also legal, ethical, and international cooperation efforts.