Next-generation Digital Forensics Challenges and Evidence Preservation Framework for IoT Devices Next-generation Digital Forensics Challenges Section Original Research


Pankaj Sharma


The proliferation of the Internet of Things devices in today’s environment generates huge amount of information about users and surroundings. Data produced by IoT devices attracts cybercriminals to perform malicious activity. The technologies like cloud and fog computing are emerging as the next-generation infrastructure for Internet of Things which may be challenging for digital investigation. In this paper, IoT and fog-based frameworks for digital forensics of IoT devices are explained and tools used in different levels of IoT such as physical level, cloud level, network level, and mobile application level are briefly discussed. The process of evidence collection and challenges in IoT forensics paradigms are well studied. For securing the extracted artifacts IoT evidence preservation framework is proposed (IoT-EvPF). Furthermore, the forensic challenges in a cloud computing environment and anti-forensics techniques used by cybercriminals to hide their identity and malicious activity are discussed. We have identified research gaps and provided a framework to encourage more thought and conversation about the difficulties of retrieving digital evidence from Fog Computing systems.


Author Biography

Lalit kumar Awasthi

Prof. Lalit Kumar Awasthi


National Institute of Technology, Uttarakhand (India)

Email: [email protected] , [email protected]

How to Cite
Sharma, P., & Awasthi, L. kumar. (2023). Next-generation Digital Forensics Challenges and Evidence Preservation Framework for IoT Devices: Next-generation Digital Forensics Challenges. International Journal of Next-Generation Computing, 14(3).


  1. AL-MASRI, E., BAI, Y., AND LI, J. 2018. A fog-based digital forensics investigation framework for IoT systems. Proceedings - 3rd IEEE International Conference on Smart Cloud, SmartCloud 2018, Institute of Electrical and Electronics Engineers Inc., 196–201. DOI:
  2. ALRUWAILI, F.F. 2021. Custodyblock: A distributed chain of custody evidence framework. Information (Switzerland) 12, 2, 1–12. DOI:
  3. ANUSH LAKSHMAN, S. AND EBENEZER, D. 2021. Integration of internet of things and drones and its future applications. Materials Today: Proceedings, Elsevier Ltd, 944–949. DOI:
  4. AROOJ, A., FAROOQ, M.S., AKRAM, A., IQBAL, R., SHARMA, A., AND DHIMAN, G. 2022. Big Data Processing and Analysis in Internet of Vehicles: Architecture, Taxonomy, and Open Research Challenges. Archives of Computational Methods in Engineering 29, 793–829. DOI:
  5. ATLAM, H.F., EL-DIN HEMDAN, E., ALENEZI, A., ALASSAFI, M.O., AND WILLS, G.B. 2020. Internet of Things Forensics: A Review. Internet of Things 11, May, 100220. DOI:
  6. ATZORI, L., IERA, A., AND MORABITO, G. 2010. The Internet of Things: A survey. Computer Networks 54, 15, 2787–2805. DOI:
  7. BANDIL, A. AND AL-MASRI, E. 2020. VTA-IH: A Fog-based Digital Forensics Framework. 2020 6th International Conference on Science in Information Technology: Embracing Industry 4.0: Towards Innovation in Disaster Management, ICSITech 2020, Institute of Electrical and Electronics Engineers Inc., 103–108. DOI:
  8. CHEEMA, S.M., ALI, M., PIRES, I.M., GONÇALVES, N.J., NAQVI, M.H., AND HASSAN, M. 2022. IoAT Enabled Smart Farming: Urdu Language-Based Solution for Low-Literate Farmers. Agriculture 12, 8, 1277. DOI:
  9. CHEN, S., ZHAO, C., HUANG, L., YUAN, J., AND LIU, M. 2020. Study and implementation on the application of blockchain in electronic evidence generation. Forensic Science International: Digital Investigation 35, 301001. DOI:
  10. CORALLO, A., LAZOI, M., LEZZI, M., AND LUPERTO, A. 2022. Cybersecurity awareness in the context of the Industrial Internet of Things: A systematic literature review. Computers in Industry 137. DOI:
  11. DUAN, H., ZHENG, Y., WANG, C., AND YUAN, X. 2019. Treasure collection on foggy islands: Building secure network archives for internet of things. IEEE Internet of Things Journal 6, 2, 2637–2650. DOI:
  12. GARFINKEL, S. 2007. Anti-Forensics: Techniques, Detection and Countermeasures. .
  13. GOODISON, S.E., DAVIS, R.C., AND JACKSON, B.A. 2015. Digital Evidence and the U.S Criminal Justice System. .
  14. GUNDERSEN, J.H. 2022. Digital forensics on fog-based IoT devices. .
  15. HANDIGOL, N., HELLER, B., JEYAKUMAR, V., MAZÌ, D., AND MCKEOWN, N. I Know What Your Packet Did Last Hop: Using Packet Histories to Troubleshoot Networks. .
  16. HEGARTY, R. AND TAYLOR, M. 2021. Digital evidence in fog computing systems. Computer Law and Security Review 41. DOI:
  17. HERENCSAR, N. 2022. Proliferation of Internet-of-Things Devices in Consumer Technologies. IEEE Consumer Electronics Magazine 11, 3, 4–5. DOI:
  18. HERMAN, M., IORGA, M., SALIM, A.M., ET AL. 2020. NIST cloud computing forensic science challenges. Gaithersburg, MD. DOI:
  19. HOU, J., LI, Y., YU, J., AND SHI, W. 2020. A Survey on Digital Forensics in Internet of Things. IEEE Internet of Things Journal 7, 1–15. DOI:
  20. IORGA, M., FELDMAN, L., BARTON, R., MARTIN, M.J., GOREN, N., AND MAHMOUDI, C. 2018. Fog computing conceptual model. Gaithersburg, MD. DOI:
  21. JAISWAL, C., NATH, M., AND KUMAR, V. 2014. Location-based security framework for cloud perimeters. IEEE Cloud Computing 1, 3, 56–64. DOI:
  22. JIA, C. AND DONG, F. 2022. Research on Intelligent collar animal husbandry health diagnosis service platform based on Cloud Computing. Institute of Electrical and Electronics Engineers (IEEE), 489–493. DOI:
  23. KEBANDE, V.R. AND RAY, I. 2016. A generic digital forensic investigation framework for Internet of Things (IoT). Proceedings - 2016 IEEE 4th International Conference on Future Internet of Things and Cloud, FiCloud 2016, 356–362. DOI:
  24. KHAN, M.N.A., ULLAH, S.W., KHAN, A.R., AND KHAN, K. 2018. Analysis of Digital Investigation Techniques in Cloud Computing Paradigm. International Journal of Next-Generation Computing 9, 3, 251–259.
  25. LI, S., QIN, T., AND MIN, G. 2019. Blockchain-Based Digital Forensics Investigation Framework in the Internet of Things and Social Systems. IEEE Transactions on Computational Social Systems 6, 6, 1433–1441. DOI:
  26. MASON, S. 2014. Electronic evidence: A proposal to reform the presumption of reliability and hearsay. Computer Law and Security Review 30, 1, 80–84. DOI:
  27. MEFFERT, C., CLARK, D., BAGGILI, I., AND BREITINGER, F. 2017. Forensic state acquisition from internet of things (FSAIoT): A general framework and practical approach for IoT forensics through IoT device state acquisition. ACM International Conference Proceeding Series Part F1305. DOI:
  28. MELL, P.M. AND GRANCE, T. 2011. The NIST definition of cloud computing. Gaithersburg, MD. DOI:
  29. MUKHERJEE, M., MATAM, R., SHU, L., ET AL. 2017. Security and Privacy in Fog Computing: Challenges. IEEE Access 5, 19293–19304. DOI:
  30. NOURA, H.N., SALMAN, O., CHEHAB, A., AND COUTURIER, R. 2020. DistLog: A distributed logging scheme for IoT forensics. Ad Hoc Networks 98, 102061. DOI:
  31. ORIWOH, E., JAZANI, D., EPIPHANIOU, G., AND SANT, P. 2013. Internet of Things Forensics: Challenges and approaches. Proceedings of the 9th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing, COLLABORATECOM 2013, 608–615. DOI:
  32. ORIWOH, E. AND SANT, P. 2013. The forensics edge management system: A concept and design. Proceedings - IEEE 10th International Conference on Ubiquitous Intelligence and Computing, UIC 2013 and IEEE 10th International Conference on Autonomic and Trusted Computing, ATC 2013, 544–550. DOI:
  33. PAPAIOANNOU, M., KARAGEORGOU, M., MANTAS, G., ET AL. 2022. A Survey on Security Threats and Countermeasures in Internet of Medical Things (IoMT). Transactions on Emerging Telecommunications Technologies 33, 6. DOI:
  34. RIJANTO, A. 2021. Blockchain technology adoption in supply chain finance. Journal of Theoretical and Applied Electronic Commerce Research 16, 7, 3078–3098. DOI:
  35. ROMAN, R., LOPEZ, J., AND MAMBO, M. 2018. Mobile edge computing, Fog et al.: A survey and analysis of security threats and challenges. Future Generation Computer Systems 78, 680–698. DOI:
  36. SALAMA, U., YAO, L., AND PAIK, H.Y. 2022. A Multilevel Collective Framework for Internet of Things Digital Forensic Investigation. Computer 55, 2, 44–53. DOI:
  37. SHI, W., CAO, J., ZHANG, Q., LI, Y., AND XU, L. 2016. Edge Computing: Vision and Challenges. IEEE Internet of Things Journal 3, 5, 637–646. DOI:
  38. SINGH, R.M., AWASTHI, L.K., AND SIKKA, G. 2023. Towards Metaheuristic Scheduling Techniques in Cloud and Fog: An Extensive Taxonomic Review. ACM Computing Surveys 55, 3, 1–43. DOI:
  39. TADDEO, M. 2019. Is Cybersecurity a Public Good? Minds and Machines 29, 349–354. DOI:
  40. TSAI, F.C. 2021. The application of blockchain of custody in criminal investigation process. Procedia Computer Science 192, 2779–2788. DOI:
  41. TULI, S. AND JHA, N.K. 2022. DINI: data imputation using neural inversion for edge applications. Scientific Reports 12, 1. DOI:
  42. VALLENTIN VALLENTIN, M., PAXSON, V., AND SOMMER, R. 2016. VAST: A Unified Platform for Interactive Network Forensics. .
  43. WANG, Y., UEHARA, T., AND SASAKI, R. 2015. Fog computing: Issues and challenges in security and forensics. Proceedings - International Computer Software and Applications Conference, IEEE Computer Society, 53–59. DOI:
  44. YAACOUB, J.P., NOURA, H., SALMAN, O., AND CHEHAB, A. 2020. Security analysis of drones systems: Attacks, limitations, and recommendations. Internet of Things (Netherlands) 11. DOI: