Permissioned Blockchain and Deep-Learning for Secure and Efficient Data Sharing in Industrial Healthcare Systems
Kumar, Randhir; Kumar, Prabhat; Tripathi, Rakesh; Gupta, Govind P; Islam, A.K.M. Najmul; Shorfuzzaman, Mohammad (2022-03-23)
Sisältö avataan julkiseksi: 24.03.2024
Post-print / Final draft
IEEE Transactions on Industrial Informatics
School of Engineering Science
data sharing framework named PBDL. Specifically, PBDL first has a blockchain scheme to register, verify (using zero-knowledge proof) and validate the communicating entities using smart contract-based consensus mechanism. Second, the authenticated data is used to propose a novel DL scheme that combines Stacked Sparse Variational AutoEncoder (SSVAE) with Self-Attentionbased Bidirectional Long Short Term Memory (SA-BiLSTM). In this scheme, SSVAE encodes or transforms the healthcare data into new format and SA-BiLSTM identifies and improves attack detection process. The security analysis and experimental results using IoT-Botnet and ToN-IoT datasets confirms the superiority of PBDL framework over existing state-of-the-art techniques.
R. Kumar, P. Kumar, R. Tripathi, G. P. Gupta, A. K. M. N. Islam and M. Shorfuzzaman, "Permissioned Blockchain and Deep-Learning for Secure and Efficient Data Sharing in Industrial Healthcare Systems," in IEEE Transactions on Industrial Informatics, doi: 10.1109/TII.2022.3161631.
- Tieteelliset julkaisut