Storage systems must be verifiably secure, and access control must be fine grained and transparent, and must provide audit trails for modern cyber-physical and cloud ecosystems. While blockchain ensures immutability and traceability of data, it does not have the ability to make real-time authorization decisions, identify abnormal behavior, or facilitate privacy-preserving collaborative data analytics across organizations. This paper introduces SecNet, a comprehensive and layered hybrid architecture that integrates smart-contract-based authorization mechanisms, AI-powered anomaly and threat detection, encrypted off-chain storage, federated learning, and a token-based incentive layer. SecNet is based on a systematic review of twenty-one recent works from the areas of blockchain access control, federated learning, secure multi-party computation, zero-knowledge proofs, reputation systems, and healthcare data governance, the results of which form four evaluation dimensions: Access Authorization Index (AAI), Security Index (SI), Vulnerability Index (VI), and Latency Index (LI). A synthetic-data testbed is developed with 30 independent simulation runs for each system, which is used for comparison with SecNet and with a Traditional-Blockchain baseline and with a Cloud-Centralized baseline. SecNet improves the Mean Algorithmic Execution Latency by 71.9% over Traditional Blockchain and 66.7% over Cloud-Centralized, the Vulnerability Index by 79.0% over Traditional Blockchain, and the Access Authorization Index and Security Index by 68.3% and 50.2% over Traditional Blockchain baseline, respectively. Overall, the improvements are statistically significant (p < 0.001), according to Welch's ttests, and the individual contributions of AI-based access authorization and smart-contract enforcement can be determined through an ablation study. The results are seen as a repeatable, scalable and quantitatively-based model for trustworthy data sharing in distributed cyber-security ecosystems in the context of SecNet.
Si ← Normalize ; Userid, Txid, Accesslevel, Threatscore, Aai S, V, et al. SecureResponse ← GenerateResponse(SecureData).
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The cooperating modules are initialized in Algorithm 1 and an initial timestamp is stored for calculating the latency. The first authentication step is fail fast: if credentials are not granted.
5.
Selvarajan S, Srivastava G, Khadidos AO, Khadidos AO, Baza M, Alshehri A, et al. An artificial intelligence lightweight blockchain security model for security and privacy in IIoT systems. Journal of Cloud Computing. 2023;12(1).
6.
Yang Z, Chen X, He Y, Liu L, Che Y, Wang X, et al. An attribute-based access control scheme using blockchain technology for IoT data protection. High-Confidence Computing. 2024;4(3):100199.
7.
Li K. A Blockchain-Integrated Federated Learning Approach for Secure Data Sharing and Privacy Protection in Multi-Device Communication. Applied Artificial Intelligence. 2024;39(1).
8.
Waheed U, Khan SA, Masud M, Jamshed H, Jumani TA, Malik NUR. Blockchain-Based, Dynamic Attribute-Based Access Control for Smart Home Energy Systems. Energies. 2025;18(8):1973.
9.
Pei H, Yang P, Du M, Liang Z, Hu Z. Blockchain-assisted Verifiable Secure Multi-Party Data Computing. Computer Networks. 2024;253:110712.
10.
Pancari S, Rashid A, Zheng J, Patel S, Wang Y, Fu J. A Systematic Comparison between the Ethereum and Hyperledger Fabric Blockchain Platforms for Attribute-Based Access Control in Smart Home IoT Environments. Sensors. 2023;23(16):7046.
11.
Hu R, Ma Z, Li L, Zuo P, Li X, Wei J, et al. An Access Control Scheme Based on Blockchain and Ciphertext Policy-Attribute Based Encryption. Sensors. 2023;23(19):8038.
12.
Lin X, Zhang Y, Huang C, Xing B, Chen L, Hu D, et al. An Access Control System Based on Blockchain with Zero-Knowledge Rollups in High-Traffic IoT Environments. Sensors. 2023;23(7):3443.
13.
Ren S, Kim E, Lee C. A scalable blockchain-enabled federated learning architecture for edge computing. PLOS ONE. 2024;19(8):e0308991.
14.
Liu B, Tang Q. Secure Data Sharing in Federated Learning through Blockchain-Based Aggregation. Future Internet. 2024;16(4):133.
15.
Ma W, Wei X, Wang L. A Security-Oriented Data-Sharing Scheme Based on Blockchain. Applied Sciences. 2024;14(16):6940.
16.
Punia A, Gulia P, Gill NS, Ibeke E, Iwendi C, Shukla PK. A systematic review on blockchain-based access control systems in cloud environment. Journal of Cloud Computing. 2024;13(1).
17.
Sajid Ullah S, Oleshchuk V, Pussewalage HSG. A survey on blockchain envisioned attribute based access control for internet of things: Overview, comparative analysis, and open research challenges. Computer Networks. 2023;235:109994.
18.
Nakai T, Shinagawa K. Secure multi-party computation with legally-enforceable fairness. International Journal of Information Security. 2024;23(6):3609–23.
19.
Mao H, Nie T, Yu M, Dong X, Li X, Yu G. SMPTC3: Secure Multi-party Protocol Based Trusted Cross-chain Contracts. MDPI AG; 2024.
20.
Rai H, Mu G, Lu R. A Scalable Reconfigurable Network-on-Chip Architecture for Heterogeneous Multi-Core Embedded Systems. Journal of Reconfigurable Hardware Architectures and Embedded Systems. 2026;(2):26–35.
21.
Polcumpally AT, Pandey KK, Kumar A, Samadhiya A. Blockchain governance and trust: A multi-sector thematic systematic review and exploration of future research directions. Heliyon. 2024;10(12):e32975.
22.
Hemmrich S, Nissen V, Beverugen D, Pauls JDM. Blockchain-based reputation systems for business-to-business services: designing a reputation mechanism to reduce information asymmetry in professional consulting. Information Systems and e-Business Management. 2025;23(3):809–44.
23.
Li T, Zuo K, Hu P, Lv L, Ni T, Shen Z, et al. Blockchain-cloud-based secure data sharing scheme with privacy preservation for Internet of vehicles. Computer Networks. 2025;272:111674.
24.
Teo ZL, Zhang X, Yang Y, Jin L, Zhang C, Poh SSJ, et al. Privacy-Preserving Technology Using Federated Learning and Blockchain in Protecting against Adversarial Attacks for Retinal Imaging. Ophthalmology. 2025;132(4):484–94.
25.
Niu G. A Blockchain-based Secure and Privacy-Preserving Healthcare Data Management Framework with SHA-256 and PoW Consensus. Informatica. 2025;49(20).
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