As a critical element of the internet’s framework, the Domain Name System (DNS) consistently faces security vulnerabilities. This paper proposes the AIChainDNS framework, which integrates the decentralization and consensus mechanisms of blockchain with the advanced pattern recognition capabilities of deep learning to enhance DNS security. The framework’s efficacy is validated through extensive tests, where AIChainDNS exhibits superior performance: utilizing the NSL-KDD dataset, the model demonstrates an anomaly detection precision of 98.26% on the Bytedance DNS Dataset (BDD), it attains a 94.56% accuracy rate. These results demonstrate AIChainDNS’s potential to better satisfy the security demands of elite internet content providers in real-world scenarios.

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AIChainDNS: A Framework for Optimizing DNS Security Through Blockchain and Machine Learning

  • Lingshan Kong,
  • Runsi Ma,
  • Hongfeng Jia,
  • He Wang

摘要

As a critical element of the internet’s framework, the Domain Name System (DNS) consistently faces security vulnerabilities. This paper proposes the AIChainDNS framework, which integrates the decentralization and consensus mechanisms of blockchain with the advanced pattern recognition capabilities of deep learning to enhance DNS security. The framework’s efficacy is validated through extensive tests, where AIChainDNS exhibits superior performance: utilizing the NSL-KDD dataset, the model demonstrates an anomaly detection precision of 98.26% on the Bytedance DNS Dataset (BDD), it attains a 94.56% accuracy rate. These results demonstrate AIChainDNS’s potential to better satisfy the security demands of elite internet content providers in real-world scenarios.