Behind Enemy Lines: Exploring Trusted Data Stream Processing on Untrusted Systems
Behind Enemy Lines: Exploring Trusted Data Stream Processing on Untrusted Systems
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DOI：
10.1145/3292006.3300021
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发表时间：
2019-03
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影响因子：
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通讯作者：
Cory Thoma;Adam J. Lee;Alexandros Labrinidis
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文献类型：
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作者：
Cory Thoma;Adam J. Lee;Alexandros Labrinidis
数据流处理系统(DSPs)通常使用外包的第三方计算平台，对瞬时流数据执行长时间、连续的查询。然而，第三方外包可能会导致对数据提供商访问控制或隐私政策的不必要违反，因为数据可能通过不受信任的基础设施流动。为了解决这些类型的违规，数据提供商可以选择使用基于启用计算的加密的流处理技术。不幸的是，这类解决方案可能会泄露有关基础明文值的信息，减少可能执行的查询集，并带来有害的性能开销。为了缓解对DSP中加密强制访问控制的担忧，我们开发了\System，这是一种利用英特尔的软件保护扩展(SGX)来保护在不可信基础设施上处理的数据的DPS。我们证明了该系统可以执行任意查询，而泄漏的信息并不比理想的基线系统多。同时，一项广泛的评估表明，与系统中的流处理相关的开销与其计算相当，从而使许多查询能够进行加密。
Data Stream Processing Systems (DSPSs) execute long-running, continuous queries over transient streaming data, often making use of outsourced, third-party computational platforms. However, third-party outsourcing can lead to unwanted violations of data providers' access controls or privacy policies, as data potentially flows through untrusted infrastructure. To address these types of violations, data providers can elect to use stream processing techniques based upon computation-enabling encryption. Unfortunately, this class of solutions can leak information about underlying plaintext values, reduce the possible set of queries that can be executed, and come with detrimental performance overheads. To alleviate the concerns with cryptographically-enforced access controls in DSPSs, we have developed \system, a DSPS that makes use of Intel's Software Guard Extensions (SGX) to protect data being processed on untrusted infrastructure. We show that \system can execute arbitrary queries while leaking no more information than an idealized \baseline system. At the same time, an extensive evaluation shows that the overheads associated with stream processing in \system are comparable to its computation-enabling encryption counterparts for many queries.