7028CEM Digital Data Acquisition, Recovery and Analysis, CW Report Assignment Brief | Coventry University

Assignment Task

Background

IoT forensics, a specialized branch of digital forensics, focuses on the recovery and analysis of digital evidence from Internet of Things (IoT) devices to reconstruct events involving these interconnected systems. Unlike traditional digital forensics, which primarily deals with data from servers, computers, and smartphones, IoT forensics encompasses a broader spectrum of evidence sources. This includes data from smart environments such as monitoring systems, traffic lights, medical implants, and smart home devices. The diversity and ubiquity of IoT devices present unique challenges in evidence identification, collection, and analysis, necessitating specialized approaches to effectively handle the vast and varied data generated within IoT ecosystems.

The objective of this assessment is for students to investigate the unique challenges of IoT forensics and evaluate current methodologies in conducting IoT forensics. Students are expected to critically analyze existing literature to understand how IoT forensics differs from traditional digital forensics, focusing on the tools utilized, types of data analyzed, techniques and methodologies employed, and the overarching challenges encountered in this specialized area.
Instructions

Your paper should provide a detailed and technical analysis of IoT forensics, focusing on the subject rather than offering general overviews or discussing non-technical aspects. The report should follow the format of an academic research paper, including a cover page, abstract, keywords, table of contents, clear sections and subsections, a references section, and an appendix if needed. Make sure your work is unbiased and correctly cited using the APA referencing style. For guidance, refer to Coventry University's APA Referencing guide: https://libguides.coventry.ac.uk/apa/howto 

Quotations should be concise, not exceeding two lines each, and should make up less than 5% of your paper. The other 95% should be written in your own words, including paraphrased literature. This is a research paper that requires critical analysis of academic literature, so the use of generative AI tools is not allowed for this assignment. Organize your paper into clear sections, clearly presenting your analysis and conclusions. Support your conclusions with strong arguments and relevant examples. Avoid just summarizing existing literature; instead, offer critical insights. Make sure to include a reference list at the end of your paper.

Assessed Module Learning Outcomes

The Learning Outcomes for this module align to the marking criteria which can be found at the end of this brief. Ensure you understand the marking criteria to ensure successful achievement of the assessment task. The following module learning outcomes are assessed in this task:

1. Apply the knowledge and skills necessary to install, configure and effectively use state of the art digital forensic tools.
2. Conduct forensic investigations on Microsoft Windows systems and learn where and how to locate system artefacts.
3. Analyse the artefacts of data recovery that compromise the study of computer forensics. Students will examine sources of electronic evidence, search and seizure issues, hard drive geometry and physical characteristics of storage media, imaging digital evidence, and validating image file integrity.
4.  Synthesise the knowledge gained, and practical skills acquired in using the various forensic tools to exploit advanced processing options to examine evidence, examine Live and Index searching, including Regular Expressions.