{"title":"实用卷隐藏加密多映射与最佳开销和超越","authors":"Jianfeng Wang, Shifeng Sun, Tianci Li, Saiyu Qi, Xiaofeng Chen","doi":"10.1145/3548606.3559345","DOIUrl":null,"url":null,"abstract":"Encrypted multi-map (EMM), as a special case of structured encryption, has attracted extensive attention recently. However, most of EMM constructions reveal the real volumes of queried keys, which can be leveraged to launch leakage-abuse attacks, as demonstrated by Kellaris et al. in CCS 2016 and Kornaropoulos et al. in S&P 2021. In this paper, we propose a practical non-lossy volume-hiding EMM scheme, XorMM, that can achieve optimal query communication complexity with minimal storage cost. Specifically, compared to the state-of-the-art dprfMM (Patel et al. CCS 2019), the client in our scheme receives only ℓ matching results while not suffering from data loss, where ℓ is the maximum volume of all keys. In addition, the storage cost of XorMM is approximately 1.23n, where n is the total number of key/value pairs. In contrast, the query communication and storage complexity of dprfMM is 2ℓ and 2(1+α)n respectively, where 0<α<1 is a small constant. Furthermore, we initiate the study of volume-hiding EMM against malicious servers. To the best of our knowledge, we present the first verifiable volume-hiding EMM scheme, XorMM, from merely symmetric cryptographic tools. The scheme still outperforms dprfMM while supporting verifiability, the query complexity and storage overhead of which are approximately ℓ +1 and 2.46n, respectively. Finally, we implement our proposed schemes and compare them with the most efficient scheme dprfMM (Patel et al. CCS 2019). The experimental results demonstrate that both of our schemes are superior to the state-of-the-art in both search and storage cost. In particular, XorMM (resp. 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引用次数: 6
摘要
加密多映射(EMM)作为结构化加密的一种特例,近年来受到了广泛的关注。然而,大多数EMM结构揭示了查询密钥的真实数量,可以利用这些数据发起泄漏滥用攻击,如Kellaris等人在CCS 2016和Kornaropoulos等人在标准普尔2021中所展示的那样。在本文中,我们提出了一种实用的非有损卷隐藏EMM方案XorMM,它可以在最小的存储成本下实现最优的查询通信复杂度。具体来说,与最先进的dprfMM (Patel et al.)相比。CCS 2019),我们方案中的客户端只接收到r匹配结果,并且不会遭受数据丢失,其中r为所有密钥的最大体积。此外,XorMM的存储成本约为1.23n,其中n为键/值对的总数。相比之下,dprfMM的查询通信复杂度和存储复杂度分别为2 l和2(1+α)n,其中0<α<1是一个小常数。此外,我们还启动了针对恶意服务器的卷隐藏EMM的研究。据我们所知,我们提出了第一个可验证的卷隐藏EMM方案,XorMM,仅从对称加密工具。该方案在支持可验证性的同时仍优于dprfMM,其查询复杂度和存储开销分别约为1 +1和2.46n。最后,我们实现了我们提出的方案,并将它们与最有效的方案dprfMM (Patel et al.)进行了比较。CCS 2019)。实验结果表明,这两种方案在搜索和存储成本上都优于现有的方案。特别是XorMM (resp.)。VXorMM)带来76%的节省。(52%)的服务器存储成本,并实现1.8倍的加速(响应速度)。1.6倍)的搜索延迟。
Practical Volume-Hiding Encrypted Multi-Maps with Optimal Overhead and Beyond
Encrypted multi-map (EMM), as a special case of structured encryption, has attracted extensive attention recently. However, most of EMM constructions reveal the real volumes of queried keys, which can be leveraged to launch leakage-abuse attacks, as demonstrated by Kellaris et al. in CCS 2016 and Kornaropoulos et al. in S&P 2021. In this paper, we propose a practical non-lossy volume-hiding EMM scheme, XorMM, that can achieve optimal query communication complexity with minimal storage cost. Specifically, compared to the state-of-the-art dprfMM (Patel et al. CCS 2019), the client in our scheme receives only ℓ matching results while not suffering from data loss, where ℓ is the maximum volume of all keys. In addition, the storage cost of XorMM is approximately 1.23n, where n is the total number of key/value pairs. In contrast, the query communication and storage complexity of dprfMM is 2ℓ and 2(1+α)n respectively, where 0<α<1 is a small constant. Furthermore, we initiate the study of volume-hiding EMM against malicious servers. To the best of our knowledge, we present the first verifiable volume-hiding EMM scheme, XorMM, from merely symmetric cryptographic tools. The scheme still outperforms dprfMM while supporting verifiability, the query complexity and storage overhead of which are approximately ℓ +1 and 2.46n, respectively. Finally, we implement our proposed schemes and compare them with the most efficient scheme dprfMM (Patel et al. CCS 2019). The experimental results demonstrate that both of our schemes are superior to the state-of-the-art in both search and storage cost. In particular, XorMM (resp. VXorMM) brings a saving of 76% (resp. 52%) in server storage cost and achieves a speedup of 1.8x (resp. 1.6x) in search latency.