IoT Forensics Research Topics

Analyzing the forensic evidence based on Internet of Things (IoT) is to collect some evidences or the footprints left digitally for any security incidents happening in IoT environment. To get more knowledge about this technology continue reading this paper till end and know about the perspectives of this method.

1. Define IoT forensics evidenceanalysis

IoT is used in analyzing the forensic evidence by testing the digital data present in IoT devices of a network in order to recreate an event and to cope up with security. The main motive of this system is to strengthen the investigations with cybersecurity and to maintain integrity among IoT environments. To extract the evidence and to interpret it, analyst uses special tools for solving the problem created by IoT environments.

2. What is IoT forensics evidenceanalysis?

Basically IoT forensic evidence is used for constructing an event which was already held, to improve security incidents and to create timelines. By using any kind of special tools, one can extract evidences and interpret it to bring a solution for problems occurring in IoT environments. The main goal of this method is to improve security and integrity of IoT devices.

3. Where IoT forensics evidenceanalysis is used?

In this section we are going to discuss about the uses of forensics evidence from IoT. Mainly this system is used for investigations in cybersecurity, for analyzing digital data from any of the IoT devices, cloud platforms or networks. This is applicable to fight against security breaches, criminal activities or unauthorized access happening in IoT environments. It plays crucial role in legal works, which needs any kind of evidence from IoT devices for taking any legal actions.

4. Why IoT forensics evidenceanalysis is proposed? Previous Technology Issues

Moving on to the next section, here we are going to discuss about the reason for its proposal and the challenges faced by this evidence analysis technique using IoT. The applications which do forensic analysis based on IoT perform tasks like storing and analyzing the evidence collected to bring solution for the cybercrime problems. Those techniques which were present earlier focus only on security of network and management of it, but it also faces some other issues other than this, which are listed here:

Insecure in authentication process: The authentication done in earlier stages consider only the parameters like user ID, mail ID biometrics and passwords which leads to decrease in security and increase in vulnerabilities.

Hash functions complexity and security: The design and the implementation of existing technique is more complex, which increases the risk of vulnerabilities, security and hashing of evidence because of the hash collisions.

Evidence collection problems: Digital forensics in earlier techniques may be affected because of human errors like mislabeling and no proper management of evidences. These mistakes should be minimized in order to increase the reliability in the process of digital forensic.

5. Algorithms / Protocols

After knowing about the technology, uses of it and the issues faced by them in the earlier stage, now we are going to learn about the algorithms used for this technology. The algorithms provided for IoT-based forensics to overcome the previous issues faced by it are: “Actor-Critic with Experience Replay with Random Forest” (A-C with ER- RF), BLAKE 3, “Elliptic Curve Integrated Encryption Scheme” (ECIES), “Logistic Regression and Genetic optimization” (LogiGen optimizer), “Random Forest with a Rule-Based System” (RF-RBS) and “Shape Code Combination” (SCC).

6. Simulation results / Parameters

The approaches which were proposed to overcome the issues faced by IoT-based forensics in the above section are tested using different methodologies to analyze its performance. The comparison is done by using metrics like Number of evidence vs. Computational overhead, Number of devices vs. delay, Number of devices vs. Evidence verification time, Number of devices vs. Evidence insertion time, Total number of transactions vs. energy efficiency, Number of malicious packets vs. detection accuracy, Number of devices vs. Authentication time, Number of devices vs. throughput and Transactions vs. block generation time.

7. Dataset LINKS / Important URL

Here are some of the links provided for you below to gain more knowledge about IoT-based forensics which can be useful for you:

• https://ieeexplore.ieee.org/abstract/document/9295823/
• https://www.sciencedirect.com/science/article/pii/S1877050922021226/pdf?md5=b30fa75b56d2a61cc03f1a0f602174ae&pid=1-s2.0-S1877050922021226-main.pdf
• https://ieeexplore.ieee.org/iel7/6287639/6514899/09786787.pdf

8. IoT forensics evidenceanalysis Applications

In this next section we are going to discuss about the applications of IoT-based forensics technology. This system can be applied in many areas which are related with cybersecurity investigations used in finding evidences for digital footprints which might be left during a security incident. This technique is very important in legal proceedings and in providing any digital evidences for “intellectual property disputes” or cybercrimes. This can also be used as an analytical approach to find and resolve issues before it turn into any security threat related to vulnerabilities from the IoT environment. The IoT forensics is a package of security, risk management and compliance, which is serving for several industries.

9. Topology

Topology is the architecture of a network; in other words the implementation plan for IoT-based forensics technology. The topology for this system uses the algorithm of machine learning in order to provide better security for network and defense mechanism.

10. Environment

The environment is the place where there should be conditions and circumstances suitable for a particular technology to function well. This IoT-based forensics technology requires a secure and dynamic network environment.

11. Simulation Tools

Here we provide some simulation software for previous works, which is established with the usage of python software with version 3.11.4 along with NS 3 tool of 3.36 or above version.

12. Results

After complete reading this paper on IoT-based forensics technology, you have now got a clear understanding about this network and system. You are also familiar with the algorithms used in it, topologies followed by this network and also the applications of it.

IoT Forensics Research Topics

1. IoT Network Forensics based on Transport Layer
2. IoT Forensics System based on Blockchain
3. Smart Home IoT Forensics: Current Status, Challenges, and Future Directions
4. Analyzing Edge IoT Digital Forensics Tools: Cyber Attacks Reconstruction and Anti-Forensics Enhancements
5. A Comprehensive Review of Digital Forensics Frameworks for Internet of Things (IoT) Devices
6. Explainable IoT Forensics: Investigation on Digital Evidence
7. Internet of Things and Digital Forensics: Recent Studies and Challenges
8. Investigating IoT Systems Security Attacks using Network Forensics
9. Enhancing IoT Forensics through Deep Learning: Investigating Cyber-Attacks and Analyzing Big Data for Improved Security Measures
10. Digital Forensics Investigation and Incident Response in Internet of Things (IoT-DFIR): Challenges and Models
11. Collecting Channel State Information in Wi-Fi Access Points for IoT Forensics
12. A Survey of Internet of Things (IoT) Forensics Frameworks and Challenges
13. Forensics in the Internet of Things: Application Specific Investigation Model, Challenges and Future Directions
14. IoT Forensics: Analysis of Ajax Systems’ mobile app for the end user
15. Survey of Evidence Collection Methods for Internet of Things Forensics
16. CMD: Co-analyzed IoT Malware Detection and Forensics via Network and Hardware Domains
17. IoT Forensics: Investigating the Mobile App of Dahua Technology
18. Blockchain meets Internet of Things (IoT) forensics: A unified framework for IoT ecosystems
19. ProvLink-IoT: A novel provenance model for Link-Layer Forensics in IoT networks
20. An improved IoT forensic model to identify interconnectivity between things
21. IoT based Agriculture (Ag-IoT): A detailed study on Architecture, Security and Forensics
22. IoT forensics: Analysis of a HIKVISION’s mobile app
23. IoT forensic analysis: A family of experiments with Amazon Echo devices
24. Forensic analysis and security assessment of IoT camera firmware for smart homes
25. Designing a Forensic-Ready Wi-Fi Access Point for the Internet of Things
26. Digital Forensics in IoT Enabled Smart Environment: Need of the Hour
27. Blockchain-Enabled Digital Forensics for the IoT: Challenges, Features, and Current Frameworks
28. State-of-the-art in IoT forensic challenges
29. Internet of Things Security and Forensics: Concern and Challenges for Inspecting Cyber Attacks
30. Towards Internet of Things (IoT) Forensics Analysis on Intelligent Robot Vacuum Systems
31. A Framework for Storage-Accuracy Optimization of IoT Forensic Analysis
32. Feature-Sniffer: Enabling IoT Forensics in OpenWrt based Wi-Fi Access Points
33. Digital Forensics for Medical Internet of Things
34. Designing a Forensic Investigation Framework for IoT Monitoring and Modeling
35. MemInspect2: OS-Independent Memory Forensics for IoT Devices in Cybercrime Investigations
36. Framework for Analyzing Intruder Behavior of IoT Cyber Attacks Based on Network Forensics by Deploying Honeypot Technology
37. ATLE2FC: Design of an Augmented Transfer Learning Model for Explainable IoT Forensics using Ensemble Classification
38. Blockchain on Security and Forensics Management in Edge Computing for IoT: A Comprehensive Survey
39. Current Trends in Internet of Things Forensics
40. Honeycomb: A Darknet-Centric Proactive Deception Technique for Curating IoT Malware Forensic Artifacts
41. Detection of IoT Malware Based on Forensic Analysis of Network Traffic Features
42. Industrial Internet of Things (IIoT): Testbed and Datasets for Cybersecurity and Digital Forensics
43. A Blockchain Based Forensic System for IoT Sensors using MQTT Protocol
44. Security Challenges and Cyber Forensics for IoT Driven BYOD Systems
45. A Multilevel Collective Framework for Internet of Things Digital Forensic Investigation
46. A systematic literature review of Blockchain-based Internet of Things (IoT) forensic investigation process models
47. A systematic analysis on the readiness of Blockchain integration in IoT forensics
48. ProvNet-IoT: Provenance based network layer forensics in Internet of Things
49. Quantifying data volatility for IoT forensics with examples from Contiki OS
50. A forensic investigation framework for Internet of Things monitoring