A Survey on Secure and Scalable Cross-chain Provenance Techniques For Digital Forensics

Investigations of cybercrime today require forensic architectures that natively traverse multiple blockchains with ease while protecting and scaling evidence processing. Although blockchains support tamper- evident logs, their original single-chain architecture limits cross-platform interoperability and forensic scaling. Recent developments overcome these limitations such as zero-knowledge proofs supporting private but verifiable evidence verification, sharding architectures splitting state without compromising latency, and AI-based anomaly detectors identifying subtle tampering. But challenges remains like zero- knowledge proofs are computationally expensive, sharding poses intricate state-
consistency problems and AI models need to be retrained constantly, incurring operational burden. Future research needs to make these pieces work for real- time, large-scale forensic applications by designing light-weight zero-knowledge constructs, self-tuning shard governance systems and compact AI with incremental-update threads. Integrating such abilities into single frameworks will offer privacy, scalability and security, supporting forensic processes for which courts will give credit in various, changing block-chain environments.

Keywords

Cross-Chain Interoperability Digital Forensics Blockchain Provenance Security Scalability

References

1. Akbarfam, A. J., Dorai, G., & Maleki, H. (2024). Secure cross-chain provenance for digital forensics collaboration. arXiv preprint arXiv:2406.11729.
2. Tyagi, A. K., Balogun, B. F., & Tiwari, S. (2024). Role of blockchain in digital forensics: A systematic study. In Global perspectives on the
applications of computer vision in cybersecurity (pp. 197–222).
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4. Swati, V., et al. (2024). Implementation of blockchain technology in forensic evidence system. International Journal of Information Technology and Computer Engineering, 12(2), 699–707.
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11. Guo, H., et al. (2024). A framework for efficient cross-chain token transfers in blockchain networks. Journal of King Saud University - Computer and Information Sciences, 36(2), 101968.
12. Ming, L., et al. (2024). A research on cross chain and interoperation methods of fusion protocol. IET Blockchain, 4(1), 18–29.
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How to Cite

Mohankumar S D, J V N Lakshmi, Shashidhara D . (2025). A Survey on Secure and Scalable Cross-chain Provenance Techniques For Digital Forensics. IITM Journal of Management and IT, 16(2), 88-99.

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[1] 1. Akbarfam, A. J., Dorai, G., & Maleki, H. (2024). Secure cross-chain provenance for digital forensics collaboration. arXiv preprint arXiv:2406.11729.

[2] 2. Tyagi, A. K., Balogun, B. F., & Tiwari, S. (2024). Role of blockchain in digital forensics: A systematic study. In Global perspectives on the

[3] applications of computer vision in cybersecurity (pp. 197–222).

[4] 3. Xu, M., et al. (2024). Exploring blockchain technology through a modular lens: A survey. ACM Computing Surveys, 56(9), 1–39.

[5] 4. Swati, V., et al. (2024). Implementation of blockchain technology in forensic evidence system. International Journal of Information Technology and Computer Engineering, 12(2), 699–707.

[6] 5. Sevim, H. O. (2022). A survey on trustless cross-chain interoperability solutions in on-chain finance. arXiv.

[7] 6. Palaiokrassas, G., Bouraga, S., & Tassiulas, L. (2024). Machine learning on blockchain data: A systematic mapping study. arXiv preprint arXiv:2403.17081.

[8] 7. Belchior, R., et al. (2024). BUNGEE: Dependable blockchain views for interoperability. Distributed Ledger Technologies: Research and Practice, 3(1), 1–25.

[9] 8. Chen, B., et al. (2024). A comprehensive survey of blockchain scalability: Shaping inner-chain and inter-chain perspectives. arXiv

[10] preprint arXiv:2409.02968.

[11] 9. Cai, Y., et al. (2024). Enabling complete atomicity for cross-chain applications through layered state commitments. In Proceedings of the 43rd International Symposium on Reliable Distributed Systems (SRDS) (pp. 1–10). IEEE.

[12] 10. Atlam, H. F., et al. (2024). Blockchain forensics: A systematic literature review of techniques, applications, challenges, and future directions. Electronics, 13(17), 3568.

[13] 11. Guo, H., et al. (2024). A framework for efficient cross-chain token transfers in blockchain networks. Journal of King Saud University - Computer and Information Sciences, 36(2), 101968.

[14] 12. Ming, L., et al. (2024). A research on cross chain and interoperation methods of fusion protocol. IET Blockchain, 4(1), 18–29.

[15] 13. Zhang, M., et al. (2024). Security of cross-chain bridges: Attack surfaces, defenses, and open problems. In Proceedings of the 27th International Symposium on Research in Attacks, Intrusions and Defenses.

[16] 14. Chiang, J. H.-Y., et al. (2025). Post-quantum threshold ring signature

[17] applications from VOLE-in-the-head. Cryptology ePrint Archive.

[18] 15. Wang, H., Li, Y., & Zhao, X. (2024). Privacy-preserving cross-chain evidence verification using zero-knowledge proofs for digital forensics. IEEE Transactions on Information Forensics and Security, 19, 1125– 1138. doi:10.1109/TIFS.2024.3382992

[19] 16. Li, Z., Chen, M., & Sun, Y. (2023). Lightweight sharding-based cross- chain framework for scalable forensic data analysis. Future Generation Computer Systems, 152, 58–70. doi:10.1016/j.future.2023.02.018

[20] 17. Rathi, V., Singh, K., & Sharma, P. (2024). AI-driven anomaly detection for secure cross-chain digital forensics. Computers & Security, 135, 103125. doi:10.1016/j.cose.2024.103125