Practical Architectures for Deployment of Searchable Encryption in a Cloud Environment

Public cloud service providers provide an infrastructure that gives businesses and individuals access to computing power and storage space on a pay-as-you-go basis. This allows these entities to bypass the usual costs associated with having their own data centre such as: hardware, construction, air conditioning and security costs, for example, making this a cost-effective solution for data storage. If the data being stored is of a sensitive nature, encrypting it prior to outsourcing it to a public cloud is a good method of ensuring the confidentiality of the data. With the data being encrypted, however, searching over it becomes unfeasible. In this paper, we examine different architectures for supporting search over encrypted data and discuss some of the challenges that need to be overcome if these techniques are to be engineered into practical systems

Multi-authority attribute-based keyword search over encrypted cloud data

National Research Foundation (NRF) Singapore; AXA Research Fun

Extended Functionality in Verifiable Searchable Encryption

Abstract. When outsourcing the storage of sensitive data to an (un-trusted) remote server, a data owner may choose to encrypt the data beforehand to preserve confidentiality. However, it is then difficult to efficiently retrieve specific portions of the data as the server is unable to identify the relevant information. Searchable encryption has been well studied as a solution to this problem, allowing data owners and other au-thorised users to generate search queries which the server may execute over the encrypted data to identify relevant data portions. However, many current schemes lack two important properties: verifia-bility of search results, and expressive queries. We introduce Extended Verifiable Searchable Encryption (eVSE) that permits a user to verify that search results are correct and complete. We also permit verifiabl

Privacy-Preserving and Regular Language Search Over Encrypted Cloud Data

Using cloud-based storage service, users can remotely store their data to clouds but also enjoy the high quality data retrieval services, without the tedious and cumbersome local data storage and maintenance. However, the sole storage service cannot satisfy all desirable requirements of users. Over the last decade, privacy-preserving search over encrypted cloud data has been a meaningful and practical research topic for outsourced data security. The fact of remote cloud storage service that users cannot have full physical possession of their data makes the privacy data search a formidable mission. A naive solution is to delegate a trusted party to access the stored data and fulfill a search task. This, nevertheless, does not scale well in practice as the fully data access may easily yield harm for user privacy. To securely introduce an effective solution, we should guarantee the privacy of search contents, i.e., what a user wants to search, and return results, i.e., what a server returns to the user. Furthermore, we also need to guarantee privacy for the outsourced data, and bring no additional local search burden to user. In this paper, we design a novel privacy-preserving functional encryption-based search mechanism over encrypted cloud data. A major advantage of our new primitive compared with the existing public key based search systems is that it supports an extreme expressive search mode, regular language search. Our security and performance analysis show that the proposed system is provably secure and more efficient than some searchable systems with high expressiveness

Searchable atribute-based mechanism with efficiient data sharing for secure cloud storage

To date, the growth of electronic personal data leads to a trend that data owners prefer to remotely outsource their data to clouds for the enjoyment of the high-quality retrieval and storage service without worrying the burden of local data management and maintenance. However, secure share and search for the outsourced data is a formidable task, which may easily incur the leakage of sensitive personal information. Efficient data sharing and searching with security is of critical importance. This paper, for the first time, proposes a searchable attribute-based proxy re-encryption system. When compared to existing systems only supporting either searchable attribute-based functionality or attribute-based proxy re-encryption, our new primitive supports both abilities and provides flexible keyword update service. Specifically, the system enables a data owner to efficiently share his data to a specified group of users matching a sharing policy and meanwhile, the data will maintain its searchable property but also the corresponding search keyword(s) can be updated after the data sharing. The new mechanism is applicable to many real-world applications, such as electronic health record systems. It is also proved chosen ciphertext secure in the random oracle model

Secure and Reliable Data Outsourcing in Cloud Computing

The many advantages of cloud computing are increasingly attracting individuals and organizations to outsource their data from local to remote cloud servers. In addition to cloud infrastructure and platform providers, such as Amazon, Google, and Microsoft, more and more cloud application providers are emerging which are dedicated to offering more accessible and user friendly data storage services to cloud customers. It is a clear trend that cloud data outsourcing is becoming a pervasive service. Along with the widespread enthusiasm on cloud computing, however, concerns on data security with cloud data storage are arising in terms of reliability and privacy which raise as the primary obstacles to the adoption of the cloud. To address these challenging issues, this dissertation explores the problem of secure and reliable data outsourcing in cloud computing. We focus on deploying the most fundamental data services, e.g., data management and data utilization, while considering reliability and privacy assurance. The first part of this dissertation discusses secure and reliable cloud data management to guarantee the data correctness and availability, given the difficulty that data are no longer locally possessed by data owners. We design a secure cloud storage service which addresses the reliability issue with near-optimal overall performance. By allowing a third party to perform the public integrity verification, data owners are significantly released from the onerous work of periodically checking data integrity. To completely free the data owner from the burden of being online after data outsourcing, we propose an exact repair solution so that no metadata needs to be generated on the fly for the repaired data. The second part presents our privacy-preserving data utilization solutions supporting two categories of semantics - keyword search and graph query. For protecting data privacy, sensitive data has to be encrypted before outsourcing, which obsoletes traditional data utilization based on plaintext keyword search. We define and solve the challenging problem of privacy-preserving multi- keyword ranked search over encrypted data in cloud computing. We establish a set of strict privacy requirements for such a secure cloud data utilization system to become a reality. We first propose a basic idea for keyword search based on secure inner product computation, and then give two improved schemes to achieve various stringent privacy requirements in two different threat models. We also investigate some further enhancements of our ranked search mechanism, including supporting more search semantics, i.e., TF × IDF, and dynamic data operations. As a general data structure to describe the relation between entities, the graph has been increasingly used to model complicated structures and schemaless data, such as the personal social network, the relational database, XML documents and chemical compounds. In the case that these data contains sensitive information and need to be encrypted before outsourcing to the cloud, it is a very challenging task to effectively utilize such graph-structured data after encryption. We define and solve the problem of privacy-preserving query over encrypted graph-structured data in cloud computing. By utilizing the principle of filtering-and-verification, we pre-build a feature-based index to provide feature-related information about each encrypted data graph, and then choose the efficient inner product as the pruning tool to carry out the filtering procedure