In the future 6G communication era, the demand for spectrum resources will reach unprecedented heights, making dynamic spectrum allocation extremely crucial. Existing dynamic spectrum sharing technologies rely on secondary users querying databases for feedback. However, malicious secondary users can infer the location of primary users through multiple queries and use Bayesian theory to update probability, posing privacy and security threats. To address this, we propose a Blockchain-based anti-Malicious Queries (BMQ)scheme. This scheme combines Dynamic Spectrum Sharing (DSS) with blockchain technology, leveraging its decentralized, tamper-proof, and secure nature to protect privacy. The BMQ scheme ensures unaffected spectrum information queries while constructing a distributed sharing environment. Additionally, we designed a consensus mechanism to detect and prevent malicious queries by determining the legality of user behavior. This mechanism addresses Bayesian-based location inference attacks, enhancing the integration of blockchain and DSS. Privacy analysis and experimental evaluation demonstrate the scheme’s effectiveness and performance advantages.

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DSS Scheme for Anti-malicious User’s Queries Based on Blockchain

  • Yating Guo,
  • Yanbo Yang,
  • Lili Gao,
  • Jiawei Zhang,
  • Jianfeng Ma,
  • Yuqing Mao

摘要

In the future 6G communication era, the demand for spectrum resources will reach unprecedented heights, making dynamic spectrum allocation extremely crucial. Existing dynamic spectrum sharing technologies rely on secondary users querying databases for feedback. However, malicious secondary users can infer the location of primary users through multiple queries and use Bayesian theory to update probability, posing privacy and security threats. To address this, we propose a Blockchain-based anti-Malicious Queries (BMQ)scheme. This scheme combines Dynamic Spectrum Sharing (DSS) with blockchain technology, leveraging its decentralized, tamper-proof, and secure nature to protect privacy. The BMQ scheme ensures unaffected spectrum information queries while constructing a distributed sharing environment. Additionally, we designed a consensus mechanism to detect and prevent malicious queries by determining the legality of user behavior. This mechanism addresses Bayesian-based location inference attacks, enhancing the integration of blockchain and DSS. Privacy analysis and experimental evaluation demonstrate the scheme’s effectiveness and performance advantages.