Supporting secure dynamic alert zones using searchable encryption and graph embedding
Supporting secure dynamic alert zones using searchable encryption and graph embedding
复制标题
使用可搜索加密和图形嵌入支持安全动态警报区域
DOI：
10.1007/s00778-023-00803-2
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Shahabi, Cyrus
中科院分区：
文献类型：
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作者：
Shaham, Sina;Ghinita, Gabriel;Shahabi, Cyrus
近年来，基于位置的警报越来越受欢迎，无论是在医疗保健（例如，COVID-19接触者追踪）、营销（例如，基于位置的广告）还是公共安全领域。然而，当位置数据在这个过程中被使用时，严重的隐私问题就出现了。一些解决方案采用可搜索加密（SE）来直接在加密位置上实现加密。虽然这样做可以保护隐私，但产生的性能开销很高。我们重点研究了公钥设置隐藏向量加密中的一种突出的SE技术，并提出了一种图嵌入技术来对位置数据进行编码，从而显著提高了对密文的处理性能。我们证明了最优编码是NP-hard的，并且我们提供了三种获得显著性能提升的启发式方法：灰色优化器、多种子灰色优化器和缩放灰色优化器。此外，我们还研究了更具挑战性的动态警报区域，其中感兴趣的区域随时间变化。我们广泛的实验评估表明，与现有基线相比，我们的解决方案可以显着改善计算开销。
Location-based alerts have gained increasing popularity in recent years, whether in the context of healthcare (e.g., COVID-19 contact tracing), marketing (e.g., location-based advertising), or public safety. However, serious privacy concerns arise when location data are used in clear in the process. Several solutions employ searchable encryption (SE) to achievesecurealerts directly on encrypted locations. While doing so preserves privacy, the performance overhead incurred is high. We focus on a prominent SE technique in the public-key setting–hidden vector encryption, and propose a graph embedding technique to encode location data in a way that significantly boosts the performance of processing on ciphertexts. We show that the optimal encoding is NP-hard, and we provide three heuristics that obtain significant performance gains: gray optimizer, multi-seed gray optimizer and scaled gray optimizer. Furthermore, we investigate the more challenging case of dynamic alert zones, where the area of interest changes over time. Our extensive experimental evaluation shows that our solutions can significantly improve computational overhead compared to existing baselines.