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A Novel Proximity Based Searchable Encryption Scheme Using Referential Dissimilarity

机译：一种使用参照异化的基于新的基于近似的可搜索的加密方案

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Outsourcing of sensitive and critical data into third party thus untrusted service environments remains a serious security concern. In such environments, data needs to be protected throughout its lifecycle i.e. atrest, in-transít and while-in-use. Data in third phase remains mostly unprotected as it demands operations to be performed over encrypted data while achieving semantics same as in case of plaintext data. This is a big challenge and thus data remains vulnerable in third phase when hosted in above environments. In this paper, we propose a novel solution to this challenge. We present a scheme on proximity-based-search on encrypted data when a majority of research is limited to exact-keyword-search only. We propose a novel scheme for proximity-based-search on encrypted databases hosted in untrusted service environments. This scheme involves a trusted proxy which facilitates a trapdoor to execute search queries over encrypted data while achieving perfect secrecy as well. It implements an idea of transitive Referential Dissimilarity over byte distances for each corresponding pair of bytes: in any two given words. This technique is based on Levenshtein Distance. To the best of our knowledge, such a scheme has been proposed for the first time and it presents a two-point novelty. Firstly, it supports basic OLTP operations securely and seamlessly as evident in presented performance statistics. Secondly, it remains provably secure and practical towards real world application requirements as it does not demand any modifications to existing ecosystems.
机译：因此，将敏感和关键数据的外包成为第三方，因此不受信任的服务环境仍然是一个严重的安全问题。在这样的环境中，需要在整个生命周期内保护数据I.E.TEST，IN-Transít和insi使用。第三阶段中的数据仍然是不受保护的，因为它要求在加密数据上执行的操作，同时实现与明文数据相同的语义相同。这是一个很大的挑战，因此当在上述环境中托管时，数据在第三阶段仍然易受攻击。在本文中，我们向这一挑战提出了一种新的解决方案。我们在大多数研究仅限于精确关键字搜索时，我们介绍了基于近似的加密数据的搜索方案。我们提出了一种新颖的基于托管的基于加密数据库的方案，在不可信任的服务环境中托管的加密数据库。该方案涉及可信赖的代理，该代理促进了一个Trapdoor来在加密数据上执行搜索查询，同时也实现完美的保密。它实现了对每个对应的字节对的字节距离的传递参考不相似性的想法：在任何两个给定的单词中。该技术基于Levenshtein距离。据我们所知，这种计划是第一次提出的，它提出了两点新奇。首先，它在呈现性能统计数据中安全地支持基本的OLTP运营，并且可以在显而易见。其次，它对现实世界的应用要求保持了证实和实用，因为它不要求对现有生态系统进行任何修改。

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