In data structures, a range query consists of preprocessing some input data into a data structure to efficiently answer any number of queries on any subset of the input. Particularly, there is a group of problems that have been extensively studied where the input is an array of unsorted numbers and a query consists of computing some function on a specific range of the array. In this article we
We present a range of novel attacks which exploit information about the volume of answers to range queries in encrypted database. Our attacks rely on a strategy which is simple yet robust and effective. We illustrate the robustness of our strategy in a number of ways. tion queries on encrypted data. Processing range queries requires the ability to compare a ciphertext data value with the encrypted query range boundary values. This can be achieved by providing the cloud rough information about the data [1,8,9,14] or building obfuscated index structures in the cloud [4,18]. Processing aggregation queries is Specifically, we analyze the data partitioning (bucketization) technique and algorithmically develop this technique to build privacy-preserving indices on sensitive attributes of a relational table. Such indices enable an untrusted server to evaluate obfuscated range queries with minimal information leakage. (point of interest) queries in privacy preserving manner [2]. To support spatial range query, an LBS user and provider should maintain minimum POIs queries by using PIR technique. But, recently CTS (coordinate transformation suite) is one of the techniques wherein it used to generate a encrypted query and calculates the (of the index) and semantic security (of the encrypted dataset). Our solution, PINED-RQ develops algorithms for building and updating the differentially private index. Compared to state-of-the-art secure index based range query processing approaches, PINED-RQ executes queries in the order of at least one magni-tude faster. Dec 28, 2018 · In this paper, we introduce and analyze methods to support range queries under the local variant of differential privacy, an emerging standard for privacy-preserving data analysis. The local model requires that each user releases a noisy view of her private data under a privacy guarantee.
various numeric-related range queries. Security analysis shows that privacy of numerical information is strongly protected against cloud providers in our proposed scheme. Index Terms—database, range query, privacy preserving, cloud computing I. INTRODUCTION T HE growing industry of cloud has provide a service
Index T erms —privacy-preserving, Boolean range queries, en- non-leaf node of the index tree, it stores the token vectors of. its bounding area and a Bloom filter B of all textual keywords. Split the query into two parts Insecure query that runs on the server Secure query that runs on the client Bucketization for range queries Larger buckets → more privacy Smaller buckets → more performance Want: maximum privacy and performance Reality: tradeoff between privacy and performance With knowledge of Bucketization scheme Probability Mar 22, 2018 · In this paper, we investigate new privacy-preserving indexing and query processing protocols which meet a number of desirable properties, including the multi-keyword query processing with conjunction and disjunction logic queries, practically high privacy guarantees with adaptive chosen keyword attack (CKA2) security and forward privacy, the Nov 27, 2019 · A privacy-preserving index for range queries. In: Thirtieth International Conference on Very Large Data Bases VLDB Endowment, pp 720–731. ACM, Toronto (2004)
Jan 01, 2020 · To extract the value behind EHRs while protecting the privacy, privacy-preserving range query has been regarded as an important issue in cloud-based eHealth systems , . Order-preserving encryption is an efficient and privacy-preserving method for range query, which jointly considers efficiency and security .
Achieving fully privacy-preserving private range queries Aug 01, 2017 A Privacy-Preserving Index for Range Queries - CORE Specifically, we analyze the data partitioning (bucketization) technique and algorithmically develop this technique to build privacy-preserving indices on sensitive attributes of a relational table. Such indices enable an untrusted server to evaluate obfuscated range queries with minimal information leakage. Privacy Preserving Location Based Spatial Range Query over (point of interest) queries in privacy preserving manner [2]. To support spatial range query, an LBS user and provider should maintain minimum POIs queries by using PIR technique. But, recently CTS (coordinate transformation suite) is one of the techniques wherein it used to generate a encrypted query and calculates the Privacy-preserving max/min query in two-tiered wireless