Secure Keyword Search Research Articles

On the Security of Secure Keyword Search and Data Sharing Mechanism for Cloud Computing

On the Security of Secure Keyword Search and Data Sharing Mechanism for Cloud Computing

Survey on Secure Keyword Search over Outsourced Data: From Cloud to Blockchain-assisted Architecture

Secure keyword search is a prevailing search service offered in outsourced environments. However, with the increasingly severe security vulnerabilities of conventional centralized outsourcing, the architecture of secure keyword search, with searchable encryption (SE) as the underlying technique, has recently shifted from cloud-centered models to blockchain-assisted models. Existing surveys commonly fail to capture such an evolution and the corresponding benefits. What on earth does blockchain bring about and what are the unexplored challenges? This survey provides a systematic review of secure keyword search over outsourced data from cloud to blockchain-assisted architectures. We propose a taxonomy assorting present studies, depending on whether cloud/blockchain and data sharing are included, in which blockchain-assisted architecture is further divided into blockchain-side and cloud-side keyword search, respectively. Technically, we conclude five types of representative SE techniques with fitting architectures, either cryptographic-based or hardware-dependent. Notably, we propose comprehensive methodologies to select relevant papers, discuss, and compare existing schemes regarding functionalities, security, efficiency, and fairness (up to 21 compared items). Finally, open issues and potential research directions are identified for future work. We aspire to help pave the way for addressing the theoretical and empirical aspects of secure keyword search and full-fledged real-world implementation of blockchain-based keyword search applications.

SecSkyline: Fast Privacy-Preserving Skyline Queries Over Encrypted Cloud Databases

The well-known benefits of cloud computing have spurred the popularity of database service outsourcing, where one can resort to the cloud to conveniently store and query databases. Coming with such popular trend is the threat to data privacy, as the cloud gains access to the databases and queries which may contain sensitive information, like medical or financial data. A large body of work has been presented for querying encrypted databases, which has been mostly focused on secure keyword search. In this paper, we instead focus on the support for secure skyline query processing over encrypted outsourced databases, where little work has been done. Skyline query is an advanced kind of database query which is important for multi-criteria decision-making systems and applications. We propose SecSkyline, a new system framework building on lightweight cryptography for fast privacy-preserving skyline queries. SecSkyline ambitiously provides strong protection for not only the content confidentiality of the outsourced database, the query, and the result, but also for data patterns that may incur indirect data leakages, such as dominance relationships among data points and search access patterns. Extensive experiments demonstrate that SecSkyline is substantially superior to the state-of-the-art in query latency, with up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$813\times$</tex-math></inline-formula> improvement.

A Security-Enhanced Query Result Verification Scheme for Outsourced Data in Location-Based Services

Location-based services (LBSs) facilitate people’s lives; location-based service providers (LBSPs) usually outsource services to third parties to provide better services. However, the third party is a dishonest entity that might return incorrect or incomplete query results under the consideration of saving storage space and computation resources. In this paper, we propose a security-enhanced query result verification scheme (SEQRVS) for the outsourced data in a LBS. Specifically, while retaining fine-grained query result verification, we improve the construction process of verification objects to enhance the security of the outsourced data. To prevent the third party from deducing the knowledge of the outsourced data stored in itself (statistically), our scheme designs a novel storage structure to enhance the ability of privacy preservation for the outsourced data. Furthermore, based on the secure keyword search and query result verification mode proposed in our scheme, the user cannot only verify the correctness and completeness of the query result but also achieve consistency verification by the blockchain. Finally, the security analysis and extensive simulation results show the security and practicality of the proposed scheme.

Secure And Dynamic Multi Keyword Ranked Search

Nowadays, information storing in third party storage is increased. Outsourcing the data to other storage device or servers which may questioned to the secure environment. However, sensitive data like medical information should need an privacy when it is stored in cloud storage. In this paper, a secure keyword search which provide the resultant data in a encrypted form where the end user can decrypt using the key given to them. It uses the Blowfish to encrypt the data and it also supports the data owner to delete or modify the content of their document. It also ensure accurate relevance score calculation between encrypted index and query vectors.

Forward and backward secure keyword search with flexible keyword shielding

Dynamic Searchable Symmetric Encryption (DSSE) has gained increasing popularity as it enables users to perform both file updates and ciphertext retrieval over encrypted data. However, existing DSSE schemes still lead to privacy leakage (e.g., forward and backward privacy) in the dynamic setting. Some forward and backward secure DSSE schemes have been proposed, but still cannot support the keyword shielding flexibly. To solve this challenging issue, we propose a Forward and Backward Authorized Keyword Search (FB-AKS) scheme with recoverable keyword shielding by using trapdoor permutations and puncturable encryption in this paper. Compared with existing forward and backward private schemes, FB-AKS achieves keyword authorization flexibly (e.g., keyword shielding, keyword un-shielding). The formal security analysis proves that FB-AKS achieves forward and backward security. And extensive experiments demonstrate that FB-AKS has less computation and storage overheads.

Secure and Dynamic Multi-Keyword Ranked Search

Nowadays, information storing in third party storage is increased. Outsourcing the data to other storage device or servers which may questioned to the secure environment. However, sensitive data like medical information should need an privacy when it is stored in cloud storage. In this paper, a secure keyword search which provide the resultant data in a encrypted form where the end user can decrypt using the key given to them. It uses the Blowfish to encrypt the data and it also supports the data owner to delete or modify the content of their document. It also ensure accurate relevance score calculation between encrypted index and query vectors.

Secure and Verifiable Keyword Search in Multiple Clouds

Searchable encryption enables users to perform a keyword-based search over encrypted data. Most of the existing searchable encryption schemes are based on the single cloud server model, which has some limitations, such as the single point of failure and malicious insiders. In contrast, the multicloud server model has higher data availability and security. However, directly moving the existing keyword search schemes to the multicloud would cause larger storage and search costs, and the data security cannot be distinctly improved. In addition, different from single cloud, a challenge is how to effectively verify query integrity when some cloud servers return incorrect or incomplete results in a multicloud situation. To ensure the data security, we propose an iterative encryption method to ensure the file privacy even if multiple cloud servers collude with each other. We use Bloom filter to map keywords and construct a tree index for each cloud server to achieve secure and efficient distributed keyword search. To verify the query integrity, we propose a fast verification algorithm to embed the file content and index information into the file ID. The analysis and experiments demonstrate the security and effectiveness of our scheme.

Enhance manet usability for encrypted data retrieval from cloud computing

&lt;p&gt;Cloud computing has become a revolutionary computing model which provides an economical and flexible strategy for resource sharing and data management. Due to privacy concerns, sensitive data has to be encrypted before being uploaded to the cloud servers. Over the last few years, several keyword searchable encryption works have been described in the literature. However, existing works mostly focus on secure searching using keyword and only retrieve Boolean results that are not yet adequate. On the other hand, poor-resources of mobile networks play an important role on all applications area nowadays. Mobile nodes mostly act as information retrieval end which make it important to address this problem. In this paper, we present a secure keyword search scheme based on the Bloom filter(SKS-BF), which enhances the system’s usability by allowing ranking based on the relevance score of the search results and retrieves the top most relevant files instead of retrieving all the files. Further, the Bloom filter (BFs) can accelerate a search process involving a large number of keywords. Extensive experiments and network simulation confirm the efficiency of our proposed schemes.&lt;/p&gt;

A Key-Policy Searchable Attribute-Based Encryption Scheme for Efficient Keyword Search and Fine-Grained Access Control over Encrypted Data

Attribute based encryption is a promising technique that achieves flexible and fine-grained data access control over encrypted data, which is very suitable for a secure data sharing environment such as the currently popular cloud computing. However, traditional attribute based encryption fails to provide an efficient keyword based search on encrypted data, which somewhat weakens the power of this encryption technique, as search is usually the most important approach to quickly obtain data of interest from large-scale dataset. To address this problem, attribute based encryption with keyword search (ABKS) is designed to achieve fine-grained data access control and keyword based search, simultaneously, by an ingenious combination of attribute based encryption and searchable encryption. Recently, several ABKS schemes have been constructed in secure cloud storage system for data access control and keyword search. Nonetheless, each of these schemes has some defects such as impractical computation overhead and insufficient access policy expression. To overcome these limitations, in this paper, we design a Key-Policy Searchable Attribute-based Encryption Scheme (KPSABES) based on the full-blown key-policy attribute-based encryption proposed by Vipul Goyal et al. By novel design, our scheme not only inherits all advantages of that scheme but also achieves efficient and secure keyword search over encrypted data. We provide the detailed performance analyses and security proofs for our scheme. Extensive experiments demonstrated that our proposed scheme is superior in many aspects to the similar work.

Catch You if You Misbehave: Ranked Keyword Search Results Verification in Cloud Computing

With the advent of cloud computing, more and more people tend to outsource their data to the cloud. As a fundamental data utilization, secure keyword search over encrypted cloud data has attracted the interest of many researchers recently. However, most of existing researches are based on an ideal assumption that the cloud server is “curious but honest”, where the search results are not verified. In this paper, we consider a more challenging model, where the cloud server would probably behave dishonestly. Based on this model, we explore the problem of result verification for the secure ranked keyword search. Different from previous data verification schemes, we propose a novel deterrent-based scheme. With our carefully devised verification data, the cloud server cannot know which data owners, or how many data owners exchange anchor data which will be used for verifying the cloud server's misbehavior. With our systematically designed verification construction, the cloud server cannot know which data owners’ data are embedded in the verification data buffer, or how many data owners’ verification data are actually used for verification. All the cloud server knows is that, once he behaves dishonestly, he would be discovered with a high probability, and punished seriously once discovered. Furthermore, we propose to optimize the value of parameters used in the construction of the secret verification data buffer. Finally, with thorough analysis and extensive experiments, we confirm the efficacy and efficiency of our proposed schemes.

Flexible, Secure, and Reliable Data Sharing Service Based on Collaboration in Multicloud Environment

Due to the abundant storage resources and high reliability data service of cloud computing, more individuals and enterprises are motivated to outsource their data to public cloud platform and enable legal data users to search and download what they need in the outsourced dataset. However, in “Paid Data Sharing” model, some valuable data should be encrypted before outsourcing for protecting owner’s economic benefits, which is an obstacle for flexible application. Specifically, if the owner does not know who (user) will download which data files in advance and even does not know the attributes of user, he/she has to either remain online all the time or import a trusted third party (TTP) to distribute the file decryption key to data user. Obviously, making the owner always remain online is too inflexible, and wholly depending on the security of TTP is a potential risk. In this paper, we propose a flexible, secure, and reliable data sharing scheme based on collaboration in multicloud environment. For securely and instantly providing data sharing service even if the owner is offline and without TTP, we distribute all encrypted split data/key blocks together to multiple cloud service providers (CSPs), respectively. An elaborate cryptographic protocol we designed helps the owner verify the correctness of data exchange bills, which is directly related to the owner’s economic benefits. Besides, in order to support reliable data service, the erasure‐correcting code technic is exploited for tolerating multiple failures among CSPs, and we offer a secure keyword search mechanism that makes the system more close to reality. Extensive security analyses and experiments on real‐world data show that our scheme is secure and efficient.

Supporting secure keyword search in the personal cloud

The Personal Cloud paradigm has emerged as a solution that allows individuals to manage under their control the collection, usage and sharing of their data. However, by regaining the full control over their data, the users also inherit the burden of protecting it against all forms of attacks and abusive usages. The Secure Personal Cloud architecture relieves the individual from this security task by employing a secure token (i.e., a tamper-resistant hardware device) to control all the sensitive information (e.g., encryption keys, metadata, indexes) and operations (e.g., authentication, data encryption/decryption, access control, and query processing). However, secure tokens are usually equipped with extremely low RAM but have significant Flash storage capacity (Gigabytes), which raises important barriers for embedded data management. This paper presents a new embedded search engine specifically designed for secure tokens, which applies to the important use-case of managing and securing documents in the Personal Cloud context. Conventional search engines privilege either insertion or query scalability but cannot meet both requirements at the same time. Moreover, very few solutions support data deletions and updates in this context. In this paper, we introduce three design principles, namely Write-Once Partitioning, Linear Pipelining and Background Linear Merging, and show how they can be combined to produce an embedded search engine matching the hardware constraints of secure tokens and reconciling high insert/delete/update rate and query scalability. Our experimental results, obtained with a prototype running on a representative hardware platform, demonstrate the scalability of the approach on large datasets and its superiority compared to state of the art methods. Finally, we also discuss the integration of our solution in another important real use-case related to performing information retrieval in smart objects.

An extended chaotic maps-based keyword search scheme over encrypted data resist outside and inside keyword guessing attacks in cloud storage services

In this paper, we propose an extended chaotic maps-based keyword search scheme over encrypted data resist outside and inside keyword guessing attacks in cloud storage services, which achieves the essential requirements of a secure cloud storage service. A secure cloud storage service has to satisfy five security requirements: consistency, ciphertext indistinguishability, trapdoor indistinguishability and resist off-line keyword guessing attacks (including off-line outside keyword guessing attack and off-line inside keyword guessing attack). Moreover, due to the characteristics of extended chaotic maps and session key establishment, which allow two communication parties to agree a common session key and the agreed session key is only known by the data sender and the authorized data receiver. Therefore, in this paper, we integrated the concept of session key establishment and extended chaotic maps into our proposed scheme which aims to resist the off-line keyword guessing attacks not only from the outside cloud attackers but also from an inside malicious cloud server. To the best of our knowledge, none of the recently proposed secure keyword search schemes can resist inside keyword guessing attacks and this work is the first attempt to provide a secure keyword search scheme without inside keyword guessing attacks in cloud storage services.

Secure deduplication storage systems supporting keyword search

Data deduplication is an attractive technology to reduce storage space for increasing vast amount of duplicated and redundant data. In a cloud storage system with data deduplication, duplicate copies of data will be eliminated and only one copy will be kept in the storage. To protect the confidentiality of sensitive data while supporting deduplication, the convergent encryption technique has been proposed to encrypt the data before outsourcing. However, the issue of keyword search over encrypted data in deduplication storage system has to be addressed for efficient data utilization. This paper firstly proposes two constructions which support secure keyword search in this scenario. In these constructions, the integrity of the data can be realized by just checking the convergent key, without other traditional integrity auditing mechanisms. Then, two extensions are presented to support fuzzy keyword search and block-level deduplication. Finally, security analysis is given.

Analysis of Some Keyword Search Schemes in Encrypted Data

With remote storage systems, a user may store his data in the encrypted form at the remote storage server to preserve confidentiality. Later, the user wants to receive his data securely through an untrusted network. The user does not want to receive all of the stored data but the data related to specific words, to reduce the communication overload in the network. In this case, we need secure and efficient keyword search schemes over the encrypted data. In the paper, we show that the keyword search schemes suggested by Byun et al. and Ballard et al. do not provide semantic security which is the most important security requirement for the keyword search schemes.