doi: 10.17586/2226-1494-2022-22-3-538-546


Efficient incremental hash chain with probabilistic filter-based method to update
blockchain light nodes

M. A. Maalla, S. V. Bezzateev


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Maalla M.A., Bezzateev S.V. Efficient incremental hash chain with probabilistic filter-based method to update blockchain light nodes. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2022, vol. 22, no. 3, pp. 538–546. doi: 10.17586/2226-1494-2022-22-3-538-546


Abstract
In blockchain, ensuring integrity of data when updating distributed ledgers is a challenging and very fundamental process. Most of blockchain networks use Merkle tree to verify the authenticity of data received from other peers on the network. However, creating Merkle tree for each block in the network and composing Merkle branch for every transaction verification request are time-consuming process requiring heavy computations. Moreover, sending these data through the network generates a lot of traffic. Therefore, we proposed an updated mechanism that uses incremental hash chain with probabilistic filter to verify block data, provide a proof of data integrity and efficiently update blockchain light nodes. In this article, we prove that our model provides better performance and less required computations than Merkle tree while maintaining the same security level.

Keywords: Merkle tree, blockchain, hash chain, probabilistic filter, hash function, integrity

References
  1. Nakamoto S. Bitcoin: A peer-to-peer electronic cash system. Decentralized Business Review, 2008, pp. 21260.
  2. Lamport L. Password authentication with insecure communication. Communications of the ACM, 1981, vol. 24, no. 11, pp. 770–772. https://doi.org/10.1145/358790.358797
  3. Merkle R.C. A digital signature based on a conventional encryption function. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1988, vol. 293, pp. 369–378. https://doi.org/10.1007/3-540-48184-2_32
  4. Wang S., Ouyang L., Yuan Y., Ni X., Han X., Wang F.-Y. Blockchain-enabled smart contracts: architecture, applications, and future trends. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2019, vol. 49, no. 11, pp. 2266–2277. https://doi.org/10.1109/TSMC.2019.2895123
  5. Das K., Bera B., Saha S., Kumar N., You I., Chao H.-C. AI-envisioned blockchain-enabled signature-based key management scheme for industrial cyber-physical systems. IEEE Internet of Things Journal, 2022, vol. 9, no. 9, pp. 6374–6388. https://doi.org/10.1109/JIOT.2021.3109314
  6. Sharma P., Jindal R., Borah M.D. Blockchain technology for cloud storage: A systematic literature review. ACM Computing Surveys, 2020, vol. 53, no. 4, pp. 3403954. https://doi.org/10.1145/3403954
  7. Hariharasitaraman S., Balakannan S.P. A dynamic data security mechanism based on position aware Merkle tree for health rehabilitation services over cloud. Journal of Ambient Intelligence and Humanized Computing, 2019, in press. https://doi.org/10.1007/s12652-019-01412-0
  8. Alzubi J.A. Blockchain-based Lamport Merkle Digital Signature: Authentication tool in IoT healthcare. Computer Communications, 2021, vol. 170, pp. 200–208. https://doi.org/10.1016/j.comcom.2021.02.002
  9. Dhumwad S., Sukhadeve M., Naik C., Manjunath K.N., Prabhu S. A peer to peer money transfer using SHA256 and Merkle tree. Proc. of the 23rd Annual International Conference in Advanced Computing and Communications (ADCOM), 2017, pp. 40–43. https://doi.org/10.1109/ADCOM.2017.00013
  10. Zhang D., Le J., Mu N., Liao X. An anonymous off-blockchain micropayments scheme for cryptocurrencies in the real world. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2020, vol. 50, no. 1, pp. 32–42. https://doi.org/10.1109/TSMC.2018.2884289
  11. Ojetunde B., Shibata N., Gao J. Secure payment system utilizing MANET for disaster areas. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2019, vol. 49, no. 12, pp. 2651–2663. https://doi.org/10.1109/TSMC.2017.2752203
  12. Zhou Z., Wang B., Dong M., Ota K. Secure and efficient vehicle-to-grid energy trading in cyber physical systems: Integration of blockchain and edge computing. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2020, vol. 50, no. 1, pp. 43–57. https://doi.org/10.1109/TSMC.2019.2896323
  13. Mao J., Zhang Y., Li P., Li T., Wu Q., Liu J. A position-aware Merkle tree for dynamic cloud data integrity verification. Soft Computing, 2017, vol. 21, no. 8, pp. 2151–2164. https://doi.org/10.1007/s00500-015-1918-8
  14. Li H., Lu R., Zhou L., Yang B., Shen X. An efficient Merkle-tree-based authentication scheme for smart grid. IEEE Systems Journal, 2014, vol. 8, no. 2, pp. 655–663. https://doi.org/10.1109/JSYST.2013.2271537
  15. Jakobsson M., Leighton T., Micali S., Szydlo M. Fractal Merkle tree representation and traversal. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2003, vol. 2612, pp. 314–326. https://doi.org/10.1007/3-540-36563-X_21
  16. Buchmann J., Dahmen E., Schneider M. Merkle tree traversal revisited. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2008, vol. 5299, pp. 63–78. https://doi.org/10.1007/978-3-540-88403-3_5
  17. Chelladurai U., Pandian S. HARE: A new hash-based authenticated reliable and efficient Modified Merkle Tree data structure to ensure integrity of data in the healthcare systems. Journal of Ambient Intelligence and Humanized Computing, 2021, in press. https://doi.org/10.1007/s12652-021-03085-0
  18. Luo L., Guo D., Ma R.T.B., Rottenstreich O., Luo X. Optimizing bloom filter: Challenges, solutions, and comparisons. IEEE Communications Surveys and Tutorials, 2019, vol. 21, no. 2, pp. 1912–1949. https://doi.org/10.1109/COMST.2018.2889329
  19. Suzuki K., Tonien D., Kurosawa K., Toyota K. Birthday paradox for multi-collisions. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2006, vol. 4296, pp. 29–40. https://doi.org/10.1007/11927587_5
  20. Gilbert H., Handschuh H. Security analysis of SHA-256 and sisters. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2004, vol. 3006, pp. 175–193. https://doi.org/10.1007/978-3-540-24654-1_13
  21. Lee D., Park N. Blockchain based privacy preserving multimedia intelligent video surveillance using secure Merkle tree. Multimedia Tools and Applications, 2021, vol. 80, no. 26-27, pp. 34517–34534. https://doi.org/10.1007/s11042-020-08776-y
  22. Kiss S.Z., Hosszu É., Tapolcai J., Rónyai L., Rottenstreich O. Bloom filter with a false positive free zone. IEEE Transactions on Network and Service Management, 2021, vol. 18, no. 2, pp. 2334–2349. https://doi.org/10.1109/TNSM.2021.3059075


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