Efficient searchble technique to retrive ranked documents in cloud

A secure searchable encryption system is presented to allow searching of encrypted user data in the cloud. The system concurrently supports fuzzy keyword searching and matched results ranking, which are two important factors in facilitating practical searchable encryption. A chaotic fuzzy conversion technique is proposed to support secure fuzzy keyword indexing, storage and query. A secure posting list is also created to rank the matched results while maintaining the privacy and confidentiality of the user data, and saving the resources of the user mobile device

SoK: Cryptographically Protected Database Search

Protected database search systems cryptographically isolate the roles of reading from, writing to, and administering the database. This separation limits unnecessary administrator access and protects data in the case of system breaches. Since protected search was introduced in 2000, the area has grown rapidly; systems are offered by academia, start-ups, and established companies. However, there is no best protected search system or set of techniques. Design of such systems is a balancing act between security, functionality, performance, and usability. This challenge is made more difficult by ongoing database specialization, as some users will want the functionality of SQL, NoSQL, or NewSQL databases. This database evolution will continue, and the protected search community should be able to quickly provide functionality consistent with newly invented databases. At the same time, the community must accurately and clearly characterize the tradeoffs between different approaches. To address these challenges, we provide the following contributions: 1) An identification of the important primitive operations across database paradigms. We find there are a small number of base operations that can be used and combined to support a large number of database paradigms. 2) An evaluation of the current state of protected search systems in implementing these base operations. This evaluation describes the main approaches and tradeoffs for each base operation. Furthermore, it puts protected search in the context of unprotected search, identifying key gaps in functionality. 3) An analysis of attacks against protected search for different base queries. 4) A roadmap and tools for transforming a protected search system into a protected database, including an open-source performance evaluation platform and initial user opinions of protected search.Comment: 20 pages, to appear to IEEE Security and Privac

Expressive Search on Encrypted Data

Different from the traditional public key encryption, search-able public key encryption allows a data owner to encrypt his data under a user’s public key in such a way that the user can generate search token keys using her secret key and then query an encryption storage server. On receiving such a search token key, the server filters all or related stored encryptions and returns matched ones as response. Searchable pubic key encryption has many promising applications. Unfortunately, existing schemes either only support simple query predicates, such as equality queries and conjunctive queries, or have a superpolynomial blowup in ciphertext size and search token key size

Searchable Symmetric Encryption and its applications

In the age of personalized advertisement and online identity profiles, people’s personal information is worth more to corporations than ever. Storing data in the cloud is increasing in popularity due to bigger file sizes and people just storing more information digitally. The leading cloud storage providers require insight into what users store on their servers. This forces users to trust their cloud storage provider not to misuse their information. This opens the possibility that private information is sold to hackers or is made publicly available on the internet. However, the more realistic case is that the service provider sells or misuses your metadata for use in personalized advertisements or other, less apparent purposes. This thesis will explore Searchable Sym- metric Encryption (SSE) algorithms and how we can utilize them to make a more secure cloud storage serviceMasteroppgave i informatikkINF399MAMN-PROGMAMN-IN

Efficient Fuzzy Search on Encrypted Data

We study the problem of efficient (sub-linear) fuzzy search on encrypted outsourced data, in the symmetric-key setting. In particular, a user who stores encrypted data on a remote untrusted server forms queries that enable the server to efficiently locate the records containing the requested keywords, even though the user may misspell keywords or provide noisy data in the query. We define an appropriate primitive for a general \emph{closeness} function on the message space that we call \emph{efficiently fuzzy-searchable encryption} (\emph{EFSE}). Next we identify an optimal security notion for EFSE. We demonstrate that existing schemes do not meet our security definition and propose a new scheme that we prove secure under basic assumptions. Unfortunately, the scheme requires large ciphertext length, but we show that, in a sense, this space-inefficiency is unavoidable for a general, optimally-secure scheme. Seeking the right balance between efficiency and security, we then show how to construct schemes that are more efficient and satisfy a weaker security notion that we propose. To illustrate, we present and analyze a more space-efficient scheme for supporting fuzzy search on biometric data that achieves the weaker notion

Secure Remote Storage of Logs with Search Capabilities

Dissertação de Mestrado em Engenharia InformáticaAlong side with the use of cloud-based services, infrastructure and storage, the use of application logs in business critical applications is a standard practice nowadays. Such application logs must be stored in an accessible manner in order to used whenever needed. The debugging of these applications is a common situation where such access is required. Frequently, part of the information contained in logs records is sensitive. This work proposes a new approach of storing critical logs in a cloud-based storage recurring to searchable encryption, inverted indexing and hash chaining techniques to achieve, in a unified way, the needed privacy, integrity and authenticity while maintaining server side searching capabilities by the logs owner. The designed search algorithm enables conjunctive keywords queries plus a fine-grained search supported by field searching and nested queries, which are essential in the referred use case. To the best of our knowledge, the proposed solution is also the first to introduce a query language that enables complex conjunctive keywords and a fine-grained search backed by field searching and sub queries.A gerac¸ ˜ao de logs em aplicac¸ ˜oes e a sua posterior consulta s˜ao fulcrais para o funcionamento de qualquer neg´ocio ou empresa. Estes logs podem ser usados para eventuais ac¸ ˜oes de auditoria, uma vez que estabelecem uma baseline das operac¸ ˜oes realizadas. Servem igualmente o prop´ osito de identificar erros, facilitar ac¸ ˜oes de debugging e diagnosticar bottlennecks de performance. Tipicamente, a maioria da informac¸ ˜ao contida nesses logs ´e considerada sens´ıvel. Quando estes logs s˜ao armazenados in-house, as considerac¸ ˜oes relacionadas com anonimizac¸ ˜ao, confidencialidade e integridade s˜ao geralmente descartadas. Contudo, com o advento das plataformas cloud e a transic¸ ˜ao quer das aplicac¸ ˜oes quer dos seus logs para estes ecossistemas, processos de logging remotos, seguros e confidenciais surgem como um novo desafio. Adicionalmente, regulac¸ ˜ao como a RGPD, imp˜oe que as instituic¸ ˜oes e empresas garantam o armazenamento seguro dos dados. A forma mais comum de garantir a confidencialidade consiste na utilizac¸ ˜ao de t ´ecnicas criptogr ´aficas para cifrar a totalidade dos dados anteriormente `a sua transfer ˆencia para o servidor remoto. Caso sejam necess´ arias capacidades de pesquisa, a abordagem mais simples ´e a transfer ˆencia de todos os dados cifrados para o lado do cliente, que proceder´a `a sua decifra e pesquisa sobre os dados decifrados. Embora esta abordagem garanta a confidencialidade e privacidade dos dados, rapidamente se torna impratic ´avel com o crescimento normal dos registos de log. Adicionalmente, esta abordagem n˜ao faz uso do potencial total que a cloud tem para oferecer. Com base nesta tem´ atica, esta tese prop˜oe o desenvolvimento de uma soluc¸ ˜ao de armazenamento de logs operacionais de forma confidencial, integra e autˆ entica, fazendo uso das capacidades de armazenamento e computac¸ ˜ao das plataformas cloud. Adicionalmente, a possibilidade de pesquisa sobre os dados ´e mantida. Essa pesquisa ´e realizada server-side diretamente sobre os dados cifrados e sem acesso em momento algum a dados n˜ao cifrados por parte do servidor..

Secure Protocols for Privacy-preserving Data Outsourcing, Integration, and Auditing

As the amount of data available from a wide range of domains has increased tremendously in recent years, the demand for data sharing and integration has also risen. The cloud computing paradigm provides great flexibility to data owners with respect to computation and storage capabilities, which makes it a suitable platform for them to share their data. Outsourcing person-specific data to the cloud, however, imposes serious concerns about the confidentiality of the outsourced data, the privacy of the individuals referenced in the data, as well as the confidentiality of the queries processed over the data. Data integration is another form of data sharing, where data owners jointly perform the integration process, and the resulting dataset is shared between them. Integrating related data from different sources enables individuals, businesses, organizations and government agencies to perform better data analysis, make better informed decisions, and provide better services. Designing distributed, secure, and privacy-preserving protocols for integrating person-specific data, however, poses several challenges, including how to prevent each party from inferring sensitive information about individuals during the execution of the protocol, how to guarantee an effective level of privacy on the released data while maintaining utility for data mining, and how to support public auditing such that anyone at any time can verify that the integration was executed correctly and no participants deviated from the protocol. In this thesis, we address the aforementioned concerns by presenting secure protocols for privacy-preserving data outsourcing, integration and auditing. First, we propose a secure cloud-based data outsourcing and query processing framework that simultaneously preserves the confidentiality of the data and the query requests, while providing differential privacy guarantees on the query results. Second, we propose a publicly verifiable protocol for integrating person-specific data from multiple data owners, while providing differential privacy guarantees and maintaining an effective level of utility on the released data for the purpose of data mining. Next, we propose a privacy-preserving multi-party protocol for high-dimensional data mashup with guaranteed LKC-privacy on the output data. Finally, we apply the theory to the real world problem of solvency in Bitcoin. More specifically, we propose a privacy-preserving and publicly verifiable cryptographic proof of solvency scheme for Bitcoin exchanges such that no information is revealed about the exchange's customer holdings, the value of the exchange's total holdings is kept secret, and multiple exchanges performing the same proof of solvency can contemporaneously prove they are not colluding

Mobile Network and Cloud Based Privacy-Preserving Data Aggregation and Processing

The emerging technology of mobile devices and cloud computing has brought a new and efficient way for data to be collected, processed and stored by mobile users. With improved specifications of mobile devices and various mobile applications provided by cloud servers, mobile users can enjoy tremendous advantages to manage their daily life through those applications instantaneously, conveniently and productively. However, using such applications may lead to the exposure of user data to unauthorised access when the data is outsourced for processing and storing purposes. Furthermore, such a setting raises the privacy breach and security issue to mobile users. As a result, mobile users would be reluctant to accept those applications without any guarantee on the safety of their data. The recent breakthrough of Fully Homomorphic Encryption (FHE) has brought a new solution for data processing in a secure motion. Several variants and improvements on the existing methods have been developed due to efficiency problems. Experience of such problems has led us to explore two areas of studies, Mobile Sensing Systems (MSS) and Mobile Cloud Computing (MCC). In MSS, the functionality of smartphones has been extended to sense and aggregate surrounding data for processing by an Aggregation Server (AS) that may be operated by a Cloud Service Provider (CSP). On the other hand, MCC allows resource-constraint devices like smartphones to fully leverage services provided by powerful and massive servers of CSPs for data processing. To support the above two application scenarios, this thesis proposes two novel schemes: an Accountable Privacy-preserving Data Aggregation (APDA) scheme and a Lightweight Homomorphic Encryption (LHE) scheme. MSS is a kind of WSNs, which implements a data aggregation approach for saving the battery lifetime of mobile devices. Furthermore, such an approach could improve the security of the outsourced data by mixing the data prior to be transmitted to an AS, so as to prevent the collusion between mobile users and the AS (or its CSP). The exposure of users’ data to other mobile users leads to a privacy breach and existing methods on preserving users’ privacy only provide an integrity check on the aggregated data without being able to identify any misbehaved nodes once the integrity check has failed. Thus, to overcome such problems, our first scheme APDA is proposed to efficiently preserve privacy and support accountability of mobile users during the data aggregation. Furthermore, APDA is designed with three versions to provide balanced solutions in terms of misbehaved node detection and data aggregation efficiency for different application scenarios. In addition, the successfully aggregated data also needs to be accompanied by some summary information based on necessary additive and non-additive functions. To preserve the privacy of mobile users, such summary could be executed by implementing existing privacy-preserving data aggregation techniques. Nevertheless, those techniques have limitations in terms of applicability, efficiency and functionality. Thus, our APDA has been extended to allow maximal value finding to be computed on the ciphertext data so as to preserve user privacy with good efficiency. Furthermore, such a solution could also be developed for other comparative operations like Average, Percentile and Histogram. Three versions of Maximal value finding (Max) are introduced and analysed in order to differentiate their efficiency and capability to determine the maximum value in a privacy-preserving manner. Moreover, the formal security proof and extensive performance evaluation of our proposed schemes demonstrate that APDA and its extended version can achieve stronger security with an optimised efficiency advantage over the state-of-the-art in terms of both computational and communication overheads. In the MCC environment, the new LHE scheme is proposed with a significant difference so as to allow arbitrary functions to be executed on ciphertext data. Such a scheme will enable rich-mobile applications provided by CSPs to be leveraged by resource-constraint devices in a privacy-preserving manner. The scheme works well as long as noise (a random number attached to the plaintext for security reasons) is less than the encryption key, which makes it flexible. The flexibility of the key size enables the scheme to incorporate with any computation functions in order to produce an accurate result. In addition, this scheme encrypts integers rather than individual bits so as to improve the scheme’s efficiency. With a proposed process that allows three or more parties to communicate securely, this scheme is suited to the MCC environment due to its lightweight property and strong security. Furthermore, the efficacy and efficiency of this scheme are thoroughly evaluated and compared with other schemes. The result shows that this scheme can achieve stronger security under a reasonable cost