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Privacy-Preserving Multi-Keyword Ranked Search over Encrypted Cloud Data,"
- Proc. IEEE INFOCOM,
, 2014
"... Abstract-With the advent of cloud computing, data owners are motivated to outsource their complex data management systems from local sites to commercial public cloud for great flexibility and economic savings. But for protecting data privacy, sensitive data has to be encrypted before outsourcing, w ..."
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Cited by 89 (10 self)
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Abstract-With the advent of cloud computing, data owners are motivated to outsource their complex data management systems from local sites to commercial public cloud for great flexibility and economic savings. But for protecting data privacy, sensitive data has to be encrypted before outsourcing, which obsoletes traditional data utilization based on plaintext keyword search. Thus, enabling an encrypted cloud data search service is of paramount importance. Considering the large number of data users and documents in cloud, it is crucial for the search service to allow multi-keyword query and provide result similarity ranking to meet the effective data retrieval need. Related works on searchable encryption focus on single keyword search or Boolean keyword search, and rarely differentiate the search results. In this paper, for the first time, we define and solve the challenging problem of privacy-preserving multi-keyword ranked search over encrypted cloud data (MRSE), and establish a set of strict privacy requirements for such a secure cloud data utilization system to become a reality. Among various multi-keyword semantics, we choose the efficient principle of "coordinate matching", i.e., as many matches as possible, to capture the similarity between search query and data documents, and further use "inner product similarity" to quantitatively formalize such principle for similarity measurement. We first propose a basic MRSE scheme using secure inner product computation, and then significantly improve it to meet different privacy requirements in two levels of threat models. Thorough analysis investigating privacy and efficiency guarantees of proposed schemes is given, and experiments on the real-world dataset further show proposed schemes indeed introduce low overhead on computation and communication.
Authorized private keyword search over encrypted data in cloud computing
, 2011
"... Abstract—In cloud computing, clients usually outsource their data to the cloud storage servers to reduce the management costs. While those data may contain sensitive personal information, the cloud servers cannot be fully trusted in protecting them. Encryption is a promising way to protect the confi ..."
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Cited by 55 (5 self)
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Abstract—In cloud computing, clients usually outsource their data to the cloud storage servers to reduce the management costs. While those data may contain sensitive personal information, the cloud servers cannot be fully trusted in protecting them. Encryption is a promising way to protect the confidentiality of the outsourced data, but it also introduces much difficulty to performing effective searches over encrypted information. Most existing works do not support efficient searches with complex query conditions, and care needs to be taken when using them because of the potential privacy leakages about the data owners to the data users or the cloud server. In this paper, using online Personal Health Record (PHR) as a case study, we first show the necessity of search capability authorization that reduces the privacy exposure resulting from the search results, and establish a scalable framework for Authorized Private Keyword Search (APKS) over encrypted cloud data. We then propose two novel solutions for APKS based on a recent cryptographic primitive, Hierarchical Predicate Encryption (HPE). Our solutions enable efficient multi-dimensional keyword searches with range query, allow delegation and revocation of search capabilities. Moreover, we enhance the query privacy which hides users ’ query keywords against the server. We implement our scheme on a modern workstation, and experimental results demonstrate its suitability for practical usage. I.
Order-Preserving Encryption Revisited: Improved Security Analysis and Alternative Solutions
, 2011
"... We further the study of order-preserving symmetric encryption (OPE), a primitive for allowing efficient range queries on encrypted data, recently initiated (from a cryptographic perspective) by Boldyreva et al. (Eurocrypt ’09). First, we address the open problem of characterizing what encryption via ..."
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Cited by 51 (1 self)
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We further the study of order-preserving symmetric encryption (OPE), a primitive for allowing efficient range queries on encrypted data, recently initiated (from a cryptographic perspective) by Boldyreva et al. (Eurocrypt ’09). First, we address the open problem of characterizing what encryption via a random order-preserving function (ROPF) leaks about underlying data (ROPF being the “ideal object ” in the security definition, POPF, satisfied by their scheme.) In particular, we show that, for a database of randomly distributed plaintexts and appropriate choice of parameters, ROPF encryption leaks neither the precise value of any plaintext nor the precise distance between any two of them. The analysis here introduces useful new techniques. On the other hand, we show that ROPF encryption leaks approximate value of any plaintext as well as approximate distance between any two plaintexts, each to an accuracy of about square root of the domain size. We then study schemes that are not order-preserving, but which nevertheless allow efficient range queries and achieve security notions stronger than POPF. In a setting where the entire database is known in advance of key-generation (considered in several prior works), we show that recent constructions of “monotone minimal perfect hash functions” allow to efficiently achieve (an adaptation of) the notion
Enabling Secure and Efficient Ranked Keyword Search over Outsourced Cloud Data
, 2010
"... Cloud computing economically enables the paradigm of data service outsourcing. However, to protect data privacy, sensitive cloud data has to be encrypted before outsourced to the commercial public cloud, which makes effective data utilization service a very challenging task. Although traditional sea ..."
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Cited by 30 (7 self)
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Cloud computing economically enables the paradigm of data service outsourcing. However, to protect data privacy, sensitive cloud data has to be encrypted before outsourced to the commercial public cloud, which makes effective data utilization service a very challenging task. Although traditional searchable encryption techniques allow users to securely search over encrypted data through keywords, they support only Boolean search and are not yet sufficient to meet the effective data utilization need that is inherently demanded by large number of users and huge amount of data files in cloud. In this paper, we define and solve the problem of secure ranked keyword search over encrypted cloud data. Ranked search greatly enhances system usability by enabling search result relevance ranking instead of sending undifferentiated results, and further ensures the file retrieval accuracy. Specifically, we explore the statistical measure approach, i.e. relevance score, from information retrieval to build a secure searchable index, and develop a one-to-many order-preserving mapping technique to properly protect those sensitive score information. The resulting design is able to facilitate efficient server-side ranking without losing keyword privacy. Thorough analysis shows that our proposed solution enjoys “as-strong-as-possible” security guarantee compared to previous searchable encryption schemes, while correctly realizing the goal of ranked keyword search. Extensive experimental results demonstrate the efficiency of the proposed solution.
Privacy preserving cloud data access with multi-authorities
- In IEEE INFOCOM
, 2013
"... Abstract—Cloud computing is a revolutionary computing paradigm which enables flexible, on-demand and low-cost usage of computing resources. Those advantages, ironically, are the causes of security and privacy problems, which emerge because the data owned by different users are stored in some cloud s ..."
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Cited by 18 (10 self)
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Abstract—Cloud computing is a revolutionary computing paradigm which enables flexible, on-demand and low-cost usage of computing resources. Those advantages, ironically, are the causes of security and privacy problems, which emerge because the data owned by different users are stored in some cloud servers instead of under their own control. To deal with security prob-lems, various schemes based on the Attribute-Based Encryption have been proposed recently. However, the privacy problem of cloud computing is yet to be solved. This paper presents an anonymous privilege control scheme AnonyControl to address not only the data privacy problem in a cloud storage, but also the user identity privacy issues in existing access control schemes. By using multiple authorities in cloud computing system, our proposed scheme achieves anonymous cloud data access and fine-grained privilege control. Our security proof and performance analysis shows that AnonyControl is both secure and efficient for cloud computing environment. I.
Efficient similarity search over encrypted data
- In Proceedings of the 2012 IEEE 28th International Conference on Data Engineering
, 2012
"... Abstract — In recent years, due to the appealing features of cloud computing, large amount of data have been stored in the cloud. Although cloud based services offer many advantages, privacy and security of the sensitive data is a big concern. To mitigate the concerns, it is desirable to outsource s ..."
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Cited by 16 (3 self)
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Abstract — In recent years, due to the appealing features of cloud computing, large amount of data have been stored in the cloud. Although cloud based services offer many advantages, privacy and security of the sensitive data is a big concern. To mitigate the concerns, it is desirable to outsource sensitive data in encrypted form. Encrypted storage protects the data against illegal access, but it complicates some basic, yet important func-tionality such as the search on the data. To achieve search over encrypted data without compromising the privacy, considerable amount of searchable encryption schemes have been proposed in the literature. However, almost all of them handle exact query matching but not similarity matching; a crucial requirement for real world applications. Although some sophisticated secure multi-party computation based cryptographic techniques are available for similarity tests, they are computationally intensive and do not scale for large data sources. In this paper, we propose an efficient scheme for similarity search over encrypted data. To do so, we utilize a state-of-the-art algorithm for fast near neighbor search in high dimensional spaces called locality sensitive hashing. To ensure the confidential-ity of the sensitive data, we provide a rigorous security definition and prove the security of the proposed scheme under the provided definition. In addition, we provide a real world application of the proposed scheme and verify the theoretical results with empirical observations on a real dataset. I.
Building Confidential and Efficient Query Services in the Cloud with RASP Data Perturbation
- IEEE Trans. Knowledge and Data Eng
, 2014
"... ar ..."
Secure top-k query processing via un trusted location-based service providers
, 2011
"... Abstract-This paper considers a novel distributed system for collaborative location-based information generation and sharing which become increasingly popular due to the explosive growth of Internet-capable and location-aware mobile devices. The system consists of a data collector, data contributors ..."
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Cited by 8 (2 self)
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Abstract-This paper considers a novel distributed system for collaborative location-based information generation and sharing which become increasingly popular due to the explosive growth of Internet-capable and location-aware mobile devices. The system consists of a data collector, data contributors, location-based service providers (LBSPs), and system users. The data collec tor gathers reviews about points-of-interest (POls) from data contributors, while LBSPs purchase POI data sets from the data collector and allow users to perform location-based top-k queries which ask for the POls in a certain region and with the highest k ratings for an interested POI attribute. In practice, LBSPs are untrusted and may return fake query results for various bad motives, e.g., in favor of POls willing to pay. This paper presents two novel schemes for users to detect fake top-k query results as an effort to foster the practical deployment and use of the proposed system. The efficacy and efficiency of our schemes are thoroughly analyzed and evaluated. I.
Toward privacy-assured cloud data services with flexible search functionalities
- in ICDCSW. IEEE
, 2012
"... Abstract—User privacy has been a major concern against the widespread adoption of the cloud technology. A full-fledged cloud data service should effectively support data utilization tasks, especially flexible data search functionalities, while simul-taneously achieve user privacy assurance and meet ..."
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Cited by 7 (1 self)
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Abstract—User privacy has been a major concern against the widespread adoption of the cloud technology. A full-fledged cloud data service should effectively support data utilization tasks, especially flexible data search functionalities, while simul-taneously achieve user privacy assurance and meet practical system-level performance requirements. In this position paper, we identify the importance and challenges of designing privacy-assured, flexible and practically efficient search mechanisms for outsourced cloud data services. In particular, we focus on two representative types of flexible search functionalities: ranked keyword search, and search over structured data. Although these functionalities are already prevalent in information retrieval in the plaintext domain, realizing them in the encrypted domain requires non-trivial effort and is relatively new. In light of this, we first describe several existing technical approaches proposed by us and other researchers, and identify their advantages and limitations. We also discuss the open research directions and provide some possible ideas for further investigation. We believe the presented results will inspire more research towards making privacy-assured search in the cloud practical and useful. I.
Order-Preserving Encryption Secure Beyond One-Wayness
"... Semantic-security of individual bits under a ciphertext are fundamental notion in modern cryptography. In this work we present the first results about this fundamental problem for Order-Preserving Encryption (OPE): “what plaintext information can be semantically hidden by OPE encryptions?” While OPE ..."
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Cited by 6 (0 self)
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Semantic-security of individual bits under a ciphertext are fundamental notion in modern cryptography. In this work we present the first results about this fundamental problem for Order-Preserving Encryption (OPE): “what plaintext information can be semantically hidden by OPE encryptions?” While OPE has gained much attention in recent years due to its usefulness in secure databases, any partial-plaintext indistinguishability (semantic security) result for it was open. Here, we propose a new indistinguishability-based security notion for OPE, which can ensure secrecy of lower bits of a plaintext (under essentially a random ciphertext probing setting). We then propose a new scheme satisfying this security notion (while earlier schemes do not satisfy it!). We note that the known security notions tell us nothing about the above partial- plaintext indistinguishability because they are limited to being one-way-based. In addition, we show that our security notion with specific parameters implies the known security notion called WOW, and further, our scheme achieves WOW with better parameters than earlier schemes.
