论文标题

$π$ QLB:具有完整性的查询语言的隐私权性

$π$QLB: A Privacy-preserving with Integrity-assuring Query Language for Blockchain

论文作者

Sohrabi, Nasrin, Rattanavipanon, Norrathep, Tari, Zahir

论文摘要

在不同的应用领域中采用区块链技术的增加,例如医疗保健系统,供应链管理,提高了对区块链数据查询机制的需求。由于当前的区块链系统缺乏对具有嵌入式安全性和隐私保证的查询数据的支持,因此存在对这些系统的固有安全性和隐私问题。特别是,现有系统要求用户在明文中向区块链操作员(例如节点验证器)提交查询。这直接危害了用户的隐私,因为提交的查询可能包含敏感信息,例如位置或性别偏好,而用户可能不舒服地共享。另一方面,目前,用户确保查询结果完整性的唯一方法是维护整个区块链数据库并在本地执行查询。这样做会给用户带来高的存储和计算成本,从而排除了这种方法实际上可以在常见的轻质设备(例如智能手机)上部署。为此,本文提出了$π$ QLB,这是一种用于区块链系统的查询语言,可确保查询输入的机密性和查询结果的完整性。此外,$π$ QLB通过将关系数据语义引入现有区块链数据库中,可以通过区块链数据启用类似SQL的查询。 $π$ QLB应用了最近的密码原始原始词,即功能秘密共享(FSS),以实现机密性。为了支持完整性,我们扩展了传统的FSS设置,以至于可以有效验证FSS结果的完整性。成功的验证表明服务器上没有恶意行为,使用户可以从结果中建立信任。据我们所知,$π$ QLB是第一个针对区块链数据库设计的查询模型,并支持机密性,完整性和类似SQL的查询。

The increase in the adoption of blockchain technology in different application domains e.g., healthcare systems, supplychain management, has raised the demand for a data query mechanism on blockchain. Since current blockchain systems lack the support for querying data with embedded security and privacy guarantees, there exists inherent security and privacy concerns on those systems. In particular, existing systems require users to submit queries to blockchain operators (e.g., a node validator) in plaintext. This directly jeopardizes users' privacy as the submitted queries may contain sensitive information, e.g., location or gender preferences, that the users may not be comfortable sharing. On the other hand, currently, the only way for users to ensure integrity of the query result is to maintain the entire blockchain database and perform the queries locally. Doing so incurs high storage and computational costs on the users, precluding this approach to be practically deployable on common light-weight devices (e.g., smartphones). To this end, this paper proposes $π$QLB, a query language for blockchain systems that ensures both confidentiality of query inputs and integrity of query results. Additionally, $π$QLB enables SQL-like queries over the blockchain data by introducing relational data semantics into the existing blockchain database. $π$QLB has applied the recent cryptography primitive, i.e., function secret sharing (FSS), to achieve confidentiality. To support integrity, we extend the traditional FSS setting in such a way that integrity of FSS results can be efficiently verified. Successful verification indicates absence of malicious behaviors on the servers, allowing the user to establish trust from the result. To the best of our knowledge, $π$QLB is the first query model designed for blockchain databases with support for confidentiality, integrity, and SQL-like queries.

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