Digital Forensics Investigation Framework Based on the Blockchain, IOT, and Social Networks


  • Vinod Kumar Uppalapu, Ajay Agarwal


blockchain, digital forensics, Internet of Things, evidence integrity, privacy preservation


Digital forensics involves the identification, preservation, analysis, and presentation of digital evidence to support legal investigations. This paper introduces a novel blockchain-based framework for digital forensics (DF) within the context of Internet of Things (IoT) and social systems. The proposed framework, named IoT forensic chain (IoTFC), capitalizes on the decentralized nature of blockchain technology to address the integrity and provenance challenges of evidence collection across jurisdictional boundaries. By leveraging blockchain's features, IoTFC ensures authenticity, immutability, traceability, resilience, and distributed trust among involved parties. The framework enhances transparency through recorded chains of blocks, covering evidence identification, preservation, analysis, and presentation. This project also presents a secured communication scheme using Blockchain for defense applications, providing privacy through message signing with corresponding private keys.


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Zhang, Y., Xu, C., Yu, S., Li, H., & Zhang, X. (2015). SCLPV: Secure certificateless public verification for cloud-based cyber-physical-social systems against malicious auditors. IEEE Transactions on Computational Social Systems, 2(4), 159-170..

Agamy, A., Ali, A. M., & Mohamed, A. M. (2020). Performance analysis of WiFi networks based on sporadic traffic model using NS3. International Journal of Mobile Network Design and Innovation, 10(1), 1-9...

Yu, B., Zhou, J., & Hu, S. (2020). Cyber-physical systems: An overview. Big data analytics for cyber-physical systems, 1-11..

Dudani, S., Baggili, I., Raymond, D., & Marchany, R. (2023). The current state of cryptocurrency forensics. Forensic Science International: Digital Investigation, 46, 301576.

Bagaa, M., Taleb, T., Bernabe, J. B., & Skarmeta, A. (2020). A machine learning security framework for iot systems. IEEE Access, 8, 114066-114077.

Li, S., Zhao, S., Yang, P., Andriotis, P., Xu, L., & Sun, Q. (2019). Distributed consensus algorithm for events detection in cyber-physical systems. IEEE Internet of Things Journal, 6(2), 2299-2308.

Hossain, M., Karim, Y., & Hasan, R. (2018, July). FIF-IoT: A forensic investigation framework for IoT using a public digital ledger. In 2018 IEEE International Congress on Internet of Things (ICIOT) (pp. 33-40). IEEE.

Zhang, Y., Wu, S., Jin, B., & Du, J. (2017, December). A blockchain-based process provenance for cloud forensics. In 2017 3rd IEEE international conference on computer and communications (ICCC) (pp. 2470-2473). IEEE.

Ryu, J. H., Sharma, P. K., Jo, J. H., & Park, J. H. (2019). A blockchain-based decentralized efficient investigation framework for IoT digital forensics. The Journal of Supercomputing, 75, 4372-4387.

Marchesi, M., Marchesi, L., & Tonelli, R. (2018, October). An agile software engineering method to design blockchain applications. In Proceedings of the 14th Central and Eastern European Software Engineering Conference Russia (pp. 1-8).

Rocha, H., & Ducasse, S. (2018, May). Preliminary steps towards modeling blockchain oriented software. In Proceedings of the 1st International Workshop on Emerging Trends in Software Engineering for Blockchain (pp. 52-57).

Kombe, C., Manyilizu, M., & Mvuma, A. (2017). Design of land administration and title registration model based on blockchain technology.




How to Cite

Ajay Agarwal, V. K. U. (2024). Digital Forensics Investigation Framework Based on the Blockchain, IOT, and Social Networks. International Journal of Intelligent Systems and Applications in Engineering, 12(21s), 1179–1182. Retrieved from



Research Article