Abstract

Background: In the field of digital forensics, the proliferation of Internet of Things (IoT) devices within intelligent residences has presented both new opportunities and challenges. Every gadget, including smart thermostats, security cameras, lighting controls, and even washing machines or refrigerators is equipped by these installers in the range of gadgets offered by manufacturers.

Methods: This research conducts a comprehensive investigation and classification of contemporary forensic tools designed for IoT devices in smart homes, highlighting their characteristics, methods of data collection, types of target devices, analytical methodologies, practical applications, and capabilities for integration. This generally involves a comparison of different forensic products or solutions and evaluation on various criteria such as cost, supportability, maintainable architecture-designs (integration), speedy acquisition speed/performance effectiveness without compromising quality, ease-of-use, and consistency. Results: A Comparative Analysis with Detailed Tables & Radar Charts Identifying the detailed pros and cons of each tool, our findings help forensic professionals understand when to use them for effective decisions. The results show that XRY and UFED by Cellebrite both scored 5/5 in each criterion, showing the best performance in mobile device forensics. Wireshark and tcpdump also have high rates for the accuracy and reliability criteria, with results of 5/5, and are therefore also highly recommended in the area of analysis of network traffic. Magnet AXIOM and NetworkMiner graded evenly well, with a usability rating of four out of five and an integration mark of 4 out of five, which diversified them for computer and mobile forensics. Splunk and ELK Stack scored topping the scalability category, with each scoring out of five, which further confirmed the analysis of logs well for large data sets. These numerical results further underline that the choice of the tool depends on specific forensic requirements.

Conclusion: The authors examine future IoT forensics in smart homes which highlights the necessity of devices working with each other through a standard and sophisticated analysis to deal with dynamic complexity development within this field.

Keywords: Smart home IoT forensics, digital forensics, IoT devices, data acquisition, forensic analysis, network traffic capture, evidence collection, incident response, forensic tools.