IoT Forensic Frameworks (DFIF, IoTDOTS, FSAIoT): a Comprehensive Study

EasyChair Preprint 9461

Abstract

In the Internet of Things, millions of electronic items, including automobiles, smoke alarms, watches, eyeglasses, webcams, and other devices, are now connected to the Internet (IoT). Aside from the luxury and comfort that the individual obtains in the field of IoT, as well as his ability to communicate and obtain information easily and quickly, the other concerning aspect is the achievement of privacy and security in this connection, especially given the rapid increase in the number of existing and new IoT devices. Concerns, threats, and assaults related to IoT security have been regarded as a potential and problematic area of research. This necessitates the quick development or creation of suitable technologies with the nature of crimes in the IoT environment. On the other hand, criminal investigation specialists encounter difficulties and hurdles due to various locations, data types, instruments used, and device recognition. This paper provides an in-depth explanation of the criminal content of the Internet of Things. It compares its stages to the detailed stages of traditional digital forensics in terms of similarities and differences, the frameworks used in dealing with electronic crimes, and the techniques used in both types. This paper presents previous discussions of researchers in the field of digital forensics. For the IoT, which brings us to the most important parts of this paper, which is a comprehensive study of the IoT criminal frameworks that are used to protect communication in the field of IoT, such as Digital Forensic Investigation Framework (DFIF), Digital Forensic Framework for Smart Environments (IoTDOTS), Forensic State Acquisition from the Internet of Things (FSAIoT), and discusses the challenges in their general frameworks and provides solutions and strategies

Keyphrases: Digital Forensic, FSAIoT, IOTDOTS, IoT, IoT Forensic, IoT challenges, IoT framework

@booklet{EasyChair:9461,
  author    = {Mohammad Hassan and Ghassan Samara and Mohammad Abu Fadda},
  title     = {IoT Forensic Frameworks (DFIF, IoTDOTS, FSAIoT): a Comprehensive Study},
  howpublished = {EasyChair Preprint 9461},
  year      = {EasyChair, 2022}}