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Design and Evaluation of a DeSci-Driven Lightweight Hybrid Blockchain Framework for Privacy-Preserving and Incentive-Aware Decentralized Healthcare Research Infrastructure Cover

Design and Evaluation of a DeSci-Driven Lightweight Hybrid Blockchain Framework for Privacy-Preserving and Incentive-Aware Decentralized Healthcare Research Infrastructure

By:  and    
Open Access
|Aug 2026

Figures & Tables

Table 1.

Comparison of the proposed framework with related work.

SystemZKP Auth.DAO GovernanceHybrid ConsensusTokenomicsDeSci Alignment
MedRec✗✗✗✗✗
FHIRChain✗✗✗✗✗
HealthChain✗✗Partial✗✗
MediCon [8]✗✗✓✗✗
Kaur et al. [13]Partial✗✗✗✗
Wang et al. [15]✗Partial✗✗Partial
Proposed✓✓✓✓✓
Figure 1:

System architecture of the proposed DeSci-driven lightweight hybrid blockchain framework for privacy-preserving and incentive-aware decentralized healthcare research.

Table 2.

Groth16 zk-SNARK parameters for the evaluated access policy circuits (2,000–5,000 gates).

ParameterValue
Proving key size (pk)8–18 MB
Verification key size (vk)~1 KB (constant)
Proof size192 bytes (constant, independent of circuit size)
Proof generation time (client-side)80–200 ms
On-chain verification time~5 ms (3 pairing operations)
Trusted setupOne-time per circuit (Powers of Tau ceremony)
Figure 2.

DAO governance proposal lifecycle state machine.

Figure 3.

End-to-end workflow of the proposed DeSci-driven framework illustrating healthcare data encryption, on-chain hash registration, off-chain storage, ZKP-based access request verification, smart contract enforcement, and DAO governance-mediated token reward distribution.

Figure 4.

ZKP-based privacy-preserving authentication architecture illustrating off-chain Groth16 zk-SNARK proof generation, on-chain smart contract verification via Verify(vk, π, C), access decision enforcement, and the zero-knowledge guarantee that no credential information is disclosed during the authentication process.

Figure 5.

Latency comparison across different network sizes.

Figure 6.

Throughput comparison of proposed and existing systems.

Table 3.

Transaction latency comparison across network sizes (ms). Lower is better.

Network Size(Nodes)Proposed (ms)MedRec (ms)FHIRChain (ms)HealthChain (ms)
10320480510455
20375628674577
30465873947779
405901,2161,3271,062
507501,6501,8101,420
Table 4.

Throughput comparison across network sizes (TPS). Higher is better.

Network Size (Nodes)Proposed (TPS)MedRec (TPS)FHIRChain (TPS)HealthChain (TPS)
10145857892
201689889107
3018510897118
40198115103126
50210130118138
Table 5.

Computational cost comparison across network sizes (AU). Lower is better.

Network Size (Nodes)Proposed (AU)MedRec (AU)FHIRChain (AU)HealthChain (AU)
10112198210185
20428780820724
309521,7421,8301,615
401,6843,0883,2402,860
502,6124,8125,0504,460
Table 6.

Qualitative feature comparison with existing systems.

FeatureProposedMedRecFHIRChainHealthChain
ZKP-based Authentication✓✗✗✗
DAO Governance✓✗✗✗
Hybrid Consensus✓✗✗Partial
Tokenomics Layer✓✗✗✗
Formal Security Proofs✓✗✗✗
DeSci Alignment✓✗✗✗
Off-chain Storage✓Partial✓Partial
Simulation Evaluated✓✓✓✓
Figure 7.

Computational cost comparison across varying network sizes.

DOI: https://doi.org/10.2478/ias-2026-0018 | Journal eISSN: 1554-1029 | Journal ISSN: 1554-1010
Language: English
Page range: 353 - 377
Published on: Aug 7, 2026
Published by: Cerebration Science Publishing Co., Limited
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open

© 2026 Garima Singh, Mohd. Haroon, published by Cerebration Science Publishing Co., Limited
This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License.