近年来，围绕基于位置服务LBS过程中的隐私泄露问题，研究人员对基于位置匿名的隐私保护方法进行了深入的研究。然而，这些研究忽略了匿名协作过程中存在的性能与安全瓶颈问题和攻击者基于语义知识进行攻击导致匿名集合隐私泄露问题。为此，结合多区块链跨链协作与k-匿名的思想，提出了一种基于多区块链协作的分布式匿名位置隐私保护方法。为了解决集中式匿名导致的隐私泄露问题，首先基于私有区块链与公有区块链的跨链协作提出了一种匿名协作用户的选择方法；其次，为了确保匿名过程中的用户协作行为的可靠性以及跨链传递数据的正确性，设计了一种匿名协作共识机制；最后，为了解决个人相关语义被忽略导致的隐私泄露问题，结合差分隐私机制与语义多样熵的匿名位置选择方法，设计了一种匿名集合构造方法。在真实数据集上的实验表明，所提方法可以有效提高位置的语义隐私安全，并在隐私性与可用性方面优于现有方法。

In recent years, researchers have conducted in-depth studies on location anonymity-based privacy protection methods amidst the issue of privacy leakage in location-based services (LBS). However, these studies overlook the performance and security bottlenecks inherent in the anonymity process during collaboration, as well as the potential for privacy leakage in anonymous sets due to attacks lever- aging semantic knowledge. To address these issues, this paper proposes a distributed anonymous location privacy protection method based on multi-blockchain collaboration, integrating the concepts of cross-chain collaboration across multiple blockchains and k-anonymity. In this approach, firstly, to tackle the privacy leakage caused by centralized anonymity, this paper present a method for selecting anonymous collaboration users based on cross-chain collaboration between private and public blockchains. Secondly, to ensure the reliability of user collaboration behavior during anonymity and the correctness of cross-chain data transmission, designing an anonymous collaboration consensus mechanism. Lastly, to mitigate privacy leakage arising from overlooked individual-related semantics,  this paper devises an anonymous set construction method that combines differential privacy mechanisms with semantic diversity entropy for selecting anonymous locations. Experiments conducted on real-world datasets demonstrate that the proposed  method can effectively enhance the semantic privacy security of locations, outperforming existing methods in terms of privacy and usability.


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