Privacy Preserving and Serverless Homomorphic-Based Searchable Encryption as a Service (SEaaS) (original) (raw)
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Since more and more data from lightweight platforms like IoT devices are being outsourced to the cloud, the need to ensure privacy while retaining data usability is important. Encrypting documents before uploading to the cloud, ensures privacy but reduces data usability. Searchable encryption, specially public-key searchable encryption (PKSE), allows secure keyword search in the cloud over encrypted documents uploaded from IoT devices. However, most existing PKSE schemes focus on returning all the files that match the queried keyword, which is not practical. To achieve a secure, practical, and efficient keyword search, we design a dynamic ranked PKSE framework over encrypted cloud data named \textit{Secure Public-Key Searchable Encryption} (Se-PKSE). We leverage a partially homomorphically encrypted index tree structure that provides sub-linear ranked search capability and allows dynamic insertion/deletion of documents without the owner storing any document details. An interactive s...
A New Secure and Lightweight Searchable Encryption Scheme over Encrypted Cloud Data
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Searchable Encryption is an emerging cryptographic technique that enables searching capabilities over the encrypted data on the cloud. In this paper, a novel searchable encryption scheme for the client-server architecture has been presented. The scheme exploits the properties of modular inverse to generate a probabilistic trapdoor which facilitates the searching over the secure inverted index table. We propose indistinguishability that is achieved by using the property of a probabilistic trapdoor. We design and implement a proof of concept prototype and test our scheme onto a real dataset of files. We analyze the performance of our scheme against our claim of the scheme being light weight. The security analysis yields that our scheme assures higher level of security as compared to other existing schemes.
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This paper presents a unified framework that supports different types of privacy-preserving search queries over encrypted cloud data. In the framework, users can perform any of the multi-keyword search, range search and k-nearest neighbor search operations in a privacypreserving manner. All three types of queries are transformed into predicate-based search leveraging bucketization, locality sensitive hashing and homomorphic encryption techniques. The proposed framework is implemented using Hadoop MapReduce, and its efficiency and accuracy are evaluated using publicly available real data sets. The implementation results show that the proposed framework can effectively be used in moderate sized data sets and it is scalable for much larger data sets provided that the number of computers in the Hadoop cluster is increased. To the best of our knowledge, the proposed framework is the first privacy-preserving solution, in which three different types of search queries are effectively applie...
Privacy-enhanced keyword search in clouds
The advent of cloud computing has dramatically changed the IT scene, as it offers cost savings and improvements to major operations. Nevertheless, the major obstacle relies on the effort on how to secure sensitive data files that are outsourced to the cloud environment. To ensure confidentiality, the sensitive data are usually encrypted prior to being outsourced. Nevertheless, effective data utilization remains a challenging task and there is a clear need for a secure and efficient searching mechanism over the encrypted data in the cloud, to increase the us-ability of the secure cloud environment. Unfortunately, existing work in the area of secure searching in the outsourcing scenario usually incur high computational complexity, which makes the approach impractical. In this paper, we take one step ahead by proposing an efficient keyword search scheme for cloud computing. Our solution is very lightweight, and it enables efficient multiuser keyword search over outsourced data files in the cloud environment, without leaking any private information about both the data owner and users in the search query. We formally define the security requirements and prove that our scheme is secure under a simple assumption in the standard model.
Secure searching on cloud storage enhanced by homomorphic indexing
Future Generation Computer Systems, 2016
h i g h l i g h t s • A searchable encryption is presented against both data and access pattern leakage. • A homomorphic exclusive-or (XOR) function is defined to enable the evaluation key to be calculated instead of storing. • An effective and feasible approach performs with a query of less than 60 milliseconds among 100,000 entries.
Keyword Search and Dual-Server Public-Key Encryption for Secure Cloud Storage
International Journal of Scientific Research in Science, Engineering and Technology, 2022
A growing number of people are interested in searchable encryption to safeguard the privacy of their data in secure searchable cloud storage. In this research, we examine the security of public key encryption with keyword search (PEKS), a widely used cryptographic fundamental with several applications in cloud storage. Unfortunately, it has been established that the conventional PEKS architecture has a flaw known as an inside keyword guessing attack (KGA) that is perpetrated by a rogue server. We suggest the dual-server PEKS framework as a new PEKS framework to remedy this security flaw (DS-PEKS). One further significant addition is the definition of a new type of smooth projective hash function (SPHF) called a linear and homomorphic SPHF (LH-SPHF). Then, using LH-SPHF, we demonstrate a generic construction of secure DS-PEKS. We propose an effective instantiation of the general framework from a Decision Diffie-Hellman-based LH-SPHF and demonstrate that it can accomplish the strong security inside the KGA to demonstrate the viability of our new framework.
Procedia Computer Science, 2020
Nowadays, cloud providers offer to their clients the possibility of storage of emails and files on the cloud server. To avoid privacy concerns, encryption should be applied to data. Unlike searching plaintext documents by keywords, encrypted documents cannot be retrieved in the same manner. As keyword searches on encrypted data are in demand, this paper describes an effective and efficient technique to support privacy-preserving keyword-based search over encrypted outsourced data. With this technique, encrypted data are first searched with the keyword, support for dynamic operations is then checked, and all relevant data documents are finally sorted based on the number of keywords matching the user query. To evaluate the technique, precision and recall are measured. The results reveal the effectiveness and efficiency of the technique in supporting privacy-preserving keyword-based search over encrypted outsourced data.
Privacy-Preserving Multiple Keyword Search on Outsourced Data in the Clouds
Lecture Notes in Computer Science, 2014
Honest but curious cloud servers can make inferences about the stored encrypted documents and the profile of a user once it knows the keywords queried by her and the keywords contained in the documents. We propose two progressively refined privacy-preserving conjunctive symmetric searchable encryption (PCSSE) schemes that allow cloud servers to perform conjunctive keyword searches on encrypted documents with different privacy assurances. Our scheme generates randomized search queries that prevent the server from detecting if the same set of keywords are being searched by different queries. It is also able to hide the number of keywords in a query as well as the number of keywords contained in an encrypted document. Our searchable encryption scheme is efficient and at the same time it is secure against the adaptive chosen keywords attack.
Searchable Symmetric Encryption for Restricted Search
Journal of Communications Software and Systems, 2018
The proliferation of cloud computing highlights the importance of techniques that permit both secure storage of sensitive data and flexible data management at the same time. One line of research with this double motivation is the study of Searchable Symmetric Encryption (SSE) that has provided several outstanding results in the recent years. These solutions achieve sublinear keyword search in huge databases by using various data structures to store keywords and document identifiers. In this work, we focus on certain scenarios in which search over the whole database is not necessary and show that the otherwise inefficient sequential scan (in linear time) can be very practical. This is due to the fact that adding new entries to the database comes for free in this case while updating a complex data structure without information leakage is rather complicated. To demonstrate the practicality of our approach we build a simple SSE scheme based on bilinear pairings and prove its security against adaptive chosen-keyword attacks in the standard model under the widely used Symmetric eXternal Diffie-Hellman (SXDH) assumption.