AI-Blockchain Integrated Trusted Interaction Mechanism... Informatica 50 (2026) 411–426 411 AI-Blockchain Integrated Trusted Interaction Mechanism for Enhanced Network Security
Abstract
This paper proposes an AI–blockchain integrated trusted interaction mechanism for network security. The mechanism combines a deep-learning anomaly detector with a permissioned blockchain and smart contracts to provide real-time threat analysis, decentralized authentication and tamper-resistant trust management. The AI module is a two-branch neural network that processes network-traffic features and interaction-behavior graphs and outputs an anomaly score for each event. The blockchain layer adopts a consortium architecture with PBFT-style consensus, and smart contracts implement identity verification, trust update rules and access control.Experiments are conducted on labeled network-traffic traces and an enterprise-like testbed. We compare the proposed mechanism with an AI-only baseline (deep model with centralized control) and a blockchain-only baseline (rule-based smart contracts without AI) using detection-level metrics—accuracy, precision, recall, F1-score, false positive rate (FPR) and false negative rate (FNR)—and system-level metrics—response time and throughput. Under low load, the system reaches 180 ms response time and 5000 requests/s throughput; under high load, response time is 300 ms and throughput is 4200 requests/s. Compared with the strongest baseline, throughput increases by 42.8% and FPR is reduced by 60.9%, while FNR remains low across diverse attack scenarios. These results confirm that the mechanism supports trusted interaction in dynamic network environments.References
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DOI:
https://doi.org/10.31449/inf.v50i12.13836Keywords:
AI Integration; Blockchain Security; Trusted Interaction;Network DefenseDownloads
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