结合区块链的车联网隐私保护可信预测缓存架构

在享受基于位置的服务(LBS, location-based service)时，用户需要频繁提交位置信息和查询请求，可能导致隐私泄露。因此，利用认知引擎感知用户需求的能力提出一种基于区块链的隐私保护缓存架构(TPCB, trusted prediction cache architecture based on blockchain)。首先，基于LSTM模型预测查询请求，请求者依靠服务提供商广播缓存数据获取服务。其次，采用信任机制评估信任值来解决与不同邻居通信时引起的交互不可信问题。最后，基于区块链的特性将交易过程中生成的大量信任数据和交易数据存储在区块中。实验结果表明TPCB能有效提高缓存命中率，并对抑制恶意提供商、激励拒绝参与的提供商和隐私保护方面具有良好的性能。

Trusted predictive cache architecture for Internet of vehicles privacy protection combined with blockchain

When enjoying location-based services, users need to submit location information and query requests frequently, which may lead to privacy disclosure. Therefore, a trusted prediction cache architecture based on blockchain(TPCB) for privacy protection is proposed by using the ability of cognitive engine to perceive user needs. First, the query request is predicted based on the LSTM model, and the requester relies on the service provider to broadcast the cached data to obtain the service. Secondly, the trust mechanism is used to evaluate the trust value to solve the problem of untrusted interaction when communicating with different neighbors. Finally, based on the characteristics of blockchain, a large number of trust data and transaction data generated in the transaction process are stored in the block. The experimental results show that TPCB can effectively improve the cache hit rate, and has good performance in restraining malicious providers, encouraging providers who refuse to participate and privacy protection.